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List per Signal Type

Learn by example

Want more? Learn by example! Here are some additional feature examples tailored for various entities:

If you are interested in integrating your own transformer models for text processing or other transformations within the FeatureByte SDK. This is done by registering a User Defined Function (UDF).

For step-by-step guidance on creating a SQL Embedding UDF, visit the Bring Your Own Transformer tutorial.

Signal types

We've organized the feature examples by entity and signal type for easier exploration.

Signal types characterize the information captured by the feature. 13 signal types are covered here:

  1. Attribute: gets the attribute of the entity at a point-in-time
  2. Frequency: counts the occurrence of events
  3. Recency: measures the time since the latest event
  4. Timing: relates to when the events happened
  5. Latest event: attributes of the latest event
  6. Stats: aggregates a numeric column's values
  7. Diversity: measures the variability of data values
  8. Stability: compares recent events to those of earlier periods
  9. Similarity: compares an individual entity feature to a group
  10. Most frequent: gets the most frequent value of a categorical column
  11. Bucketing: aggregates a column's values across categories of a categorical column.
  12. Attribute stats: collects stats for an attribute of the entity
  13. Attribute change: measures the occurrence or magnitude of changes to slowly changing attributes

Explore features for the Customer entity

Customer Signal type: Attribute

CUSTOMER_Gender: Gender of the customer

CUSTOMER_State: State of the customer

CUSTOMER_PostalCode: PostalCode of the customer

CUSTOMER_Age_band: Age Band (5 years intervals) of the customer.

Customer Signal type: Frequency

CUSTOMER_Count_of_invoice_14d: Count of invoice for the customer over a 14d period.

CUSTOMER_Count_of_item_14d: Count of item for the customer over a 14d period.

Customer Signal type: Recency

CUSTOMER_Time_Since_Latest_invoice_Timestamp: Time (in days) Since Latest invoice Timestamp for the customer

Customer Signal type: Timing

CUSTOMER_Latest_invoice_Weekday: Latest invoice Weekday for the customer

CUSTOMER_invoice_Amount_across_invoice_Weekdays_14d: Distribution representing the cumulative Amount of invoice, categorized by their respective invoice's Weekday, for the customer over a 14d period. The result is presented as a dictionary where the Weekday of invoice serves as the key and its corresponding sum of Amount forms the value.

CUSTOMER_Consistency_of_invoice_Amount_across_invoice_Weekdays_14d_vs_28d: Consistency score of the customer measured by the Cosine Similarity between the Distribution representing the cumulative Amount of invoice, categorized by their respective invoice's Weekday, for both the 14d and 28d periods.

CUSTOMER_vs_OVERALL_invoice_Amount_across_invoice_Weekdays_28d: Similarity between the customer and all customers measured by the Cosine Similarity between the Distribution representing the cumulative Amount of invoice, categorized by their respective invoice's Weekday, over 28d for both entities.

CUSTOMER_Variability_of_invoice_Weekday_based_on_invoice_Amount_28d: The feature evaluates the distribution of a customer's invoice's Amount across various invoice's Weekday categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of invoice's Amount across categories, while lower entropy suggests a concentration within specific invoice's Weekday categories.

CUSTOMER_invoice_Weekday_with_Highest_sum_of_invoice_Amount_28d: invoice Weekday with Highest sum of invoice Amount for the customer over a 28d period.

CUSTOMER_Unique_Count_of_invoice_Weekday_14d: Unique Count of invoice Weekday for the customer over a 14d period.

CUSTOMER_Max_of_Time_between_2_invoices_for_the_customer_14d: Max of Time between 2 invoices for the customer over a 14d period.

Customer Signal type: Latest event

CUSTOMER_Latest_invoice_Amount: Latest invoice Amount for the customer

CUSTOMER_Latest_INVOICE_Count_of_item: Latest INVOICE_Count_of_item for the customer

CUSTOMER_Latest_INVOICE_Sum_of_item_Discount: Latest INVOICE_Sum_of_item_Discount for the customer

Customer Signal type: Stats

CUSTOMER_Avg_of_invoice_Amount_14d: Avg of invoice Amount for the customer over a 14d period.

CUSTOMER_Max_of_invoice_Amount_14d: Max of invoice Amount for the customer over a 14d period.

CUSTOMER_Sum_of_invoice_Amount_14d: Sum of invoice Amount for the customer over a 14d period.

CUSTOMER_Avg_of_INVOICE_Count_of_item_14d: Avg of INVOICE_Count_of_item for the customer over a 14d period.

CUSTOMER_Max_of_INVOICE_Count_of_item_14d: Max of INVOICE_Count_of_item for the customer over a 14d period.

CUSTOMER_Avg_of_INVOICE_Sum_of_item_Discount_14d: Avg of INVOICE_Sum_of_item_Discount for the customer over a 14d period.

CUSTOMER_Max_of_INVOICE_Sum_of_item_Discount_14d: Max of INVOICE_Sum_of_item_Discount for the customer over a 14d period.

CUSTOMER_Avg_of_item_Quantity_14d: Avg of item Quantity for the customer over a 14d period.

CUSTOMER_Max_of_item_Quantity_14d: Max of item Quantity for the customer over a 14d period.

CUSTOMER_Sum_of_item_Quantity_14d: Sum of item Quantity for the customer over a 14d period.

CUSTOMER_Avg_of_item_UnitPrice_14d: Avg of item UnitPrice for the customer over a 14d period.

CUSTOMER_Max_of_item_UnitPrice_14d: Max of item UnitPrice for the customer over a 14d period.

CUSTOMER_Avg_of_item_TotalCost_14d: Avg of item TotalCost for the customer over a 14d period.

CUSTOMER_Max_of_item_TotalCost_14d: Max of item TotalCost for the customer over a 14d period.

CUSTOMER_Avg_of_item_Discount_14d: Avg of item Discount for the customer over a 14d period.

CUSTOMER_Max_of_item_Discount_14d: Max of item Discount for the customer over a 14d period.

CUSTOMER_Sum_of_item_Discount_14d: Sum of item Discount for the customer over a 14d period.

Customer Signal type: Diversity

CUSTOMER_Std_of_invoice_Amount_14d: Std of invoice Amount for the customer over a 14d period.

CUSTOMER_Std_of_INVOICE_Count_of_item_14d: Std of INVOICE_Count_of_item for the customer over a 14d period.

CUSTOMER_Std_of_INVOICE_Sum_of_item_Discount_14d: Std of INVOICE_Sum_of_item_Discount for the customer over a 14d period.

CUSTOMER_Std_of_item_Quantity_14d: Std of item Quantity for the customer over a 14d period.

CUSTOMER_Std_of_item_UnitPrice_14d: Std of item UnitPrice for the customer over a 14d period.

CUSTOMER_Std_of_item_TotalCost_14d: Std of item TotalCost for the customer over a 14d period.

CUSTOMER_Std_of_item_Discount_14d: Std of item Discount for the customer over a 14d period.

CUSTOMER_Variability_of_product_ProductGroup_based_on_item_TotalCost_28d: The feature evaluates the distribution of a customer's item's TotalCost across various product's ProductGroup categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific product's ProductGroup categories.

CUSTOMER_Unique_Count_of_product_ProductGroup_14d: Unique Count of product ProductGroup for the customer over a 14d period.

Customer Signal type: Stability

CUSTOMER_Consistency_of_Sum_of_invoice_Amount_14d_vs_28d: Consistency of the customer measured by the Ratio of the Sum of invoice Amount for both the 14d and 28d periods

CUSTOMER_Consistency_of_item_TotalCost_across_product_ProductGroups_14d_vs_28d: Consistency score of the customer measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, for both the 14d and 28d periods.

CUSTOMER_Consistency_of_Sum_of_item_Discount_14d_vs_28d: Consistency of the customer measured by the Ratio of the Sum of item Discount for both the 14d and 28d periods

CUSTOMER_Consistency_of_Sum_of_item_Quantity_14d_vs_28d: Consistency of the customer measured by the Ratio of the Sum of item Quantity for both the 14d and 28d periods

Customer Signal type: Similarity

CUSTOMER_vs_OVERALL_Avg_of_invoice_Amount_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of invoice Amount over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Count_of_item_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of INVOICE_Count_of_item over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_INVOICE_Sum_of_item_Discount_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of INVOICE_Sum_of_item_Discount over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_item_Quantity_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of item Quantity over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_item_UnitPrice_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of item UnitPrice over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_item_TotalCost_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of item TotalCost over 28d for both entities.

CUSTOMER_vs_OVERALL_Avg_of_item_Discount_28d: Similarity between the customer and all customers measured by the Ratio of the Avg of item Discount over 28d for both entities.

CUSTOMER_vs_OVERALL_item_TotalCost_across_product_ProductGroups_28d: Similarity between the customer and all customers measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, over 28d for both entities.

Customer Signal type: Most frequent

CUSTOMER_product_ProductGroup_with_Highest_sum_of_item_TotalCost_28d: product ProductGroup with Highest sum of item TotalCost for the customer over a 28d period.

Customer Signal type: Bucketing

CUSTOMER_item_TotalCost_across_product_ProductGroups_14d: Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, for the customer over a 14d period. The result is presented as a dictionary where the ProductGroup serves as the key and its corresponding sum of TotalCost forms the value.

Customer Signal type: Attribute change

CUSTOMER_Time_Since_Latest_Change_in_State: Time (in days) Since Latest Change in State for the customer.

CUSTOMER_Time_Since_Latest_Change_in_PostalCode: Time (in days) Since Latest Change in PostalCode for the customer.

Explore features for the Product entity

Product Signal type: Attribute

PRODUCT_ProductGroup: ProductGroup of the product

Product Signal type: Frequency

PRODUCT_Count_of_item_14d: Count of item for the product over a 14d period.

Product Signal type: Recency

PRODUCT_Time_Since_Latest_invoice_Timestamp: Time (in days) Since Latest invoice Timestamp for the product

Product Signal type: Timing

PRODUCT_item_TotalCost_across_invoice_Weekdays_14d: Distribution representing the cumulative TotalCost of item, categorized by their respective invoice's Weekday, for the product over a 14d period. The result is presented as a dictionary where the Weekday of invoice serves as the key and its corresponding sum of TotalCost forms the value.

PRODUCT_Consistency_of_item_TotalCost_across_invoice_Weekdays_14d_vs_28d: Consistency score of the product measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective invoice's Weekday, for both the 14d and 28d periods.

PRODUCT_vs_PRODUCTGROUP_item_TotalCost_across_invoice_Weekdays_28d: Similarity between the product and all products of the product productgroup measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective invoice's Weekday, over 28d for both entities.

PRODUCT_vs_OVERALL_item_TotalCost_across_invoice_Weekdays_28d: Similarity between the product and all products measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective invoice's Weekday, over 28d for both entities.

PRODUCT_Variability_of_invoice_Weekday_based_on_item_TotalCost_28d: The feature evaluates the distribution of a product's item's TotalCost across various invoice's Weekday categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific invoice's Weekday categories.

PRODUCT_invoice_Weekday_with_Highest_sum_of_item_TotalCost_28d: invoice Weekday with Highest sum of item TotalCost for the product over a 28d period.

PRODUCT_Unique_Count_of_invoice_Weekday_14d: Unique Count of invoice Weekday for the product over a 14d period.

Product Signal type: Stats

PRODUCT_Avg_of_item_Quantity_14d: Avg of item Quantity for the product over a 14d period.

PRODUCT_Max_of_item_Quantity_14d: Max of item Quantity for the product over a 14d period.

PRODUCT_Sum_of_item_Quantity_14d: Sum of item Quantity for the product over a 14d period.

PRODUCT_Avg_of_item_UnitPrice_14d: Avg of item UnitPrice for the product over a 14d period.

PRODUCT_Max_of_item_UnitPrice_14d: Max of item UnitPrice for the product over a 14d period.

PRODUCT_Avg_of_item_TotalCost_14d: Avg of item TotalCost for the product over a 14d period.

PRODUCT_Max_of_item_TotalCost_14d: Max of item TotalCost for the product over a 14d period.

PRODUCT_Sum_of_item_TotalCost_14d: Sum of item TotalCost for the product over a 14d period.

PRODUCT_Avg_of_item_Discount_14d: Avg of item Discount for the product over a 14d period.

PRODUCT_Max_of_item_Discount_14d: Max of item Discount for the product over a 14d period.

PRODUCT_Sum_of_item_Discount_14d: Sum of item Discount for the product over a 14d period.

Product Signal type: Diversity

PRODUCT_Std_of_item_Quantity_14d: Std of item Quantity for the product over a 14d period.

PRODUCT_Std_of_item_UnitPrice_14d: Std of item UnitPrice for the product over a 14d period.

PRODUCT_Std_of_item_TotalCost_14d: Std of item TotalCost for the product over a 14d period.

PRODUCT_Std_of_item_Discount_14d: Std of item Discount for the product over a 14d period.

PRODUCT_Variability_of_customer_Gender_based_on_item_TotalCost_28d: The feature evaluates the distribution of a product's item's TotalCost across various customer's Gender categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific customer's Gender categories.

PRODUCT_Unique_Count_of_customer_Gender_14d: Unique Count of customer Gender for the product over a 14d period.

PRODUCT_Variability_of_customer_State_based_on_item_TotalCost_28d: The feature evaluates the distribution of a product's item's TotalCost across various customer's State categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific customer's State categories.

PRODUCT_Unique_Count_of_customer_State_14d: Unique Count of customer State for the product over a 14d period.

PRODUCT_Variability_of_customer_PostalCode_based_on_item_TotalCost_28d: The feature evaluates the distribution of a product's item's TotalCost across various customer's PostalCode categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific customer's PostalCode categories.

PRODUCT_Unique_Count_of_customer_PostalCode_14d: Unique Count of customer PostalCode for the product over a 14d period.

PRODUCT_Variability_of_customer_Age_band_based_on_item_TotalCost_28d: The feature evaluates the distribution of a product's item's TotalCost across various customer_Age_band categories over a 28d period using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific customer_Age_band categories.

PRODUCT_Unique_Count_of_customer_Age_band_14d: Unique Count of customer_Age_band for the product over a 14d period.

Product Signal type: Stability

PRODUCT_Consistency_of_Sum_of_item_Quantity_14d_vs_28d: Consistency of the product measured by the Ratio of the Sum of item Quantity for both the 14d and 28d periods

PRODUCT_Consistency_of_item_TotalCost_across_customer_Genders_14d_vs_28d: Consistency score of the product measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer's Gender, for both the 14d and 28d periods.

PRODUCT_Consistency_of_Sum_of_item_TotalCost_14d_vs_28d: Consistency of the product measured by the Ratio of the Sum of item TotalCost for both the 14d and 28d periods

PRODUCT_Consistency_of_item_TotalCost_across_customer_Age_bands_14d_vs_28d: Consistency score of the product measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer_Age_band, for both the 14d and 28d periods.

PRODUCT_Consistency_of_Sum_of_item_Discount_14d_vs_28d: Consistency of the product measured by the Ratio of the Sum of item Discount for both the 14d and 28d periods

Product Signal type: Similarity

PRODUCT_vs_PRODUCTGROUP_Avg_of_item_Quantity_28d: Similarity between the product and all products of the product productgroup measured by the Ratio of the Avg of item Quantity over 28d for both entities.

PRODUCT_vs_OVERALL_Avg_of_item_Quantity_28d: Similarity between the product and all products measured by the Ratio of the Avg of item Quantity over 28d for both entities.

PRODUCT_vs_PRODUCTGROUP_Avg_of_item_UnitPrice_28d: Similarity between the product and all products of the product productgroup measured by the Ratio of the Avg of item UnitPrice over 28d for both entities.

PRODUCT_vs_OVERALL_Avg_of_item_UnitPrice_28d: Similarity between the product and all products measured by the Ratio of the Avg of item UnitPrice over 28d for both entities.

PRODUCT_vs_PRODUCTGROUP_Avg_of_item_TotalCost_28d: Similarity between the product and all products of the product productgroup measured by the Ratio of the Avg of item TotalCost over 28d for both entities.

PRODUCT_vs_OVERALL_Avg_of_item_TotalCost_28d: Similarity between the product and all products measured by the Ratio of the Avg of item TotalCost over 28d for both entities.

PRODUCT_vs_PRODUCTGROUP_Avg_of_item_Discount_28d: Similarity between the product and all products of the product productgroup measured by the Ratio of the Avg of item Discount over 28d for both entities.

PRODUCT_vs_OVERALL_Avg_of_item_Discount_28d: Similarity between the product and all products measured by the Ratio of the Avg of item Discount over 28d for both entities.

PRODUCT_vs_PRODUCTGROUP_item_TotalCost_across_customer_Genders_28d: Similarity between the product and all products of the product productgroup measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer's Gender, over 28d for both entities.

PRODUCT_vs_OVERALL_item_TotalCost_across_customer_Genders_28d: Similarity between the product and all products measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer's Gender, over 28d for both entities.

PRODUCT_vs_PRODUCTGROUP_item_TotalCost_across_customer_Age_bands_28d: Similarity between the product and all products of the product productgroup measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer_Age_band, over 28d for both entities.

PRODUCT_vs_OVERALL_item_TotalCost_across_customer_Age_bands_28d: Similarity between the product and all products measured by the Cosine Similarity between the Distribution representing the cumulative TotalCost of item, categorized by their respective customer_Age_band, over 28d for both entities.

Product Signal type: Most frequent

PRODUCT_customer_Gender_with_Highest_sum_of_item_TotalCost_28d: customer Gender with Highest sum of item TotalCost for the product over a 28d period.

PRODUCT_customer_State_with_Highest_sum_of_item_TotalCost_28d: customer State with Highest sum of item TotalCost for the product over a 28d period.

PRODUCT_customer_PostalCode_with_Highest_sum_of_item_TotalCost_28d: customer PostalCode with Highest sum of item TotalCost for the product over a 28d period.

PRODUCT_customer_Age_band_with_Highest_sum_of_item_TotalCost_28d: customer_Age_band with Highest sum of item TotalCost for the product over a 28d period.

Product Signal type: Bucketing

PRODUCT_item_TotalCost_across_customer_Genders_14d: Distribution representing the cumulative TotalCost of item, categorized by their respective customer's Gender, for the product over a 14d period. The result is presented as a dictionary where the Gender serves as the key and its corresponding sum of TotalCost forms the value.

PRODUCT_item_TotalCost_across_customer_Age_bands_14d: Distribution representing the cumulative TotalCost of item, categorized by their respective customer_Age_band, for the product over a 14d period. The result is presented as a dictionary where the customer_Age_band serves as the key and its corresponding sum of TotalCost forms the value.

Explore features for the Customer x Product entity

Customer x Product Signal type: Frequency

CUSTOMER_X_PRODUCT_Count_of_item_14d: Count of item for the customer_x_product over a 14d period.

Customer x Product Signal type: Recency

CUSTOMER_X_PRODUCT_Time_Since_Latest_invoice_Timestamp: Time (in days) Since Latest invoice Timestamp for the customer_x_product

Customer x Product Signal type: Timing

CUSTOMER_X_PRODUCT_Latest_invoice_Weekday: Latest invoice Weekday for the customer_x_product

Customer x Product Signal type: Latest event

CUSTOMER_X_PRODUCT_Latest_item_Quantity: Latest item Quantity for the customer_x_product

CUSTOMER_X_PRODUCT_Latest_item_UnitPrice: Latest item UnitPrice for the customer_x_product

CUSTOMER_X_PRODUCT_Latest_item_TotalCost: Latest item TotalCost for the customer_x_product

CUSTOMER_X_PRODUCT_Latest_item_Discount: Latest item Discount for the customer_x_product

Customer x Product Signal type: Stats

CUSTOMER_X_PRODUCT_Sum_of_item_Quantity_14d: Sum of item Quantity for the customer_x_product over a 14d period.

CUSTOMER_X_PRODUCT_Sum_of_item_TotalCost_14d: Sum of item TotalCost for the customer_x_product over a 14d period.

CUSTOMER_X_PRODUCT_Sum_of_item_Discount_14d: Sum of item Discount for the customer_x_product over a 14d period.

Customer x Product Signal type: Stability

CUSTOMER_X_PRODUCT_Consistency_of_Sum_of_item_Discount_14d_vs_28d: Consistency of the customer_x_product measured by the Ratio of the Sum of item Discount for both the 14d and 28d periods

CUSTOMER_X_PRODUCT_Consistency_of_Sum_of_item_TotalCost_14d_vs_28d: Consistency of the customer_x_product measured by the Ratio of the Sum of item TotalCost for both the 14d and 28d periods

CUSTOMER_X_PRODUCT_Consistency_of_Sum_of_item_Quantity_14d_vs_28d: Consistency of the customer_x_product measured by the Ratio of the Sum of item Quantity for both the 14d and 28d periods

Customer x Product Signal type: Similarity

CUSTOMER_X_PRODUCT_product_ProductGroup_Representation_in_CUSTOMER_item_TotalCost_14d: The feature assesses the representation of a given product_ProductGroup in a given CUSTOMER's item TotalCost over a 14d period. A value greater than 1 indicates this product_ProductGroup is over-represented for the particular customer. The evaluation is done by comparing: - the Percentage of a customer's total item TotalCost, that match the ProductGroup of a specific product over a 14d period. - the Percentage of the total item TotalCost, that match the ProductGroup of a specific product over a 14d period.

Explore features for the Item entity

Item Signal type: Attribute

ITEM_Quantity: Quantity of the item

ITEM_UnitPrice: UnitPrice of the item

ITEM_TotalCost: TotalCost of the item

ITEM_Discount: Discount of the item

Item Signal type: Similarity

ITEM_Quantity_Z_Score_to_PRODUCT_item_Quantity_14d: Z-Score of the item Quantity in relation to the distribution of item Quantity among all items with the same product as that item over a 14d period.

ITEM_Quantity_to_PRODUCT_item_Quantity_ratio_14d: Ratio of item Quantity to the total sum of item Quantity among all items with the same product as that item over the 14d period.

ITEM_Quantity_Z_Score_to_PRODUCTGROUP_item_Quantity_14d: Z-Score of the item Quantity in relation to the distribution of item Quantity among all items with the same productgroup as that item over a 14d period.

ITEM_Quantity_Z_Score_to_CUSTOMER_item_Quantity_14d: Z-Score of the item Quantity in relation to the distribution of item Quantity among all items with the same customer as that item over a 14d period.

ITEM_Quantity_to_CUSTOMER_item_Quantity_ratio_14d: Ratio of item Quantity to the total sum of item Quantity among all items with the same customer as that item over the 14d period.

ITEM_Quantity_Z_Score_to_CUSTOMER_X_PRODUCT_item_Quantity_14d: Z-Score of the item Quantity in relation to the distribution of item Quantity among all items with the same customer_x_product as that item over a 14d period.

ITEM_Quantity_to_CUSTOMER_X_PRODUCT_item_Quantity_ratio_14d: Ratio of item Quantity to the total sum of item Quantity among all items with the same customer_x_product as that item over the 14d period.

ITEM_Quantity_Z_Score_to_OVERALL_item_Quantity_14d: Z-Score of the item Quantity in relation to the distribution of item Quantity among all items over a 14d period.

ITEM_UnitPrice_Z_Score_to_PRODUCT_item_UnitPrice_14d: Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items with the same product as that item over a 14d period.

ITEM_UnitPrice_Z_Score_to_PRODUCTGROUP_item_UnitPrice_14d: Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items with the same productgroup as that item over a 14d period.

ITEM_UnitPrice_Z_Score_to_CUSTOMER_item_UnitPrice_14d: Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items with the same customer as that item over a 14d period.

ITEM_UnitPrice_Z_Score_to_CUSTOMER_X_PRODUCT_item_UnitPrice_14d: Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items with the same customer_x_product as that item over a 14d period.

ITEM_UnitPrice_Z_Score_to_OVERALL_item_UnitPrice_14d: Z-Score of the item UnitPrice in relation to the distribution of item UnitPrice among all items over a 14d period.

ITEM_TotalCost_Z_Score_to_PRODUCT_item_TotalCost_14d: Z-Score of the item TotalCost in relation to the distribution of item TotalCost among all items with the same product as that item over a 14d period.

ITEM_TotalCost_to_PRODUCT_item_TotalCost_ratio_14d: Ratio of item TotalCost to the total sum of item TotalCost among all items with the same product as that item over the 14d period.

ITEM_TotalCost_Z_Score_to_PRODUCTGROUP_item_TotalCost_14d: Z-Score of the item TotalCost in relation to the distribution of item TotalCost among all items with the same productgroup as that item over a 14d period.

ITEM_TotalCost_Z_Score_to_CUSTOMER_item_TotalCost_14d: Z-Score of the item TotalCost in relation to the distribution of item TotalCost among all items with the same customer as that item over a 14d period.

ITEM_TotalCost_Z_Score_to_CUSTOMER_X_PRODUCT_item_TotalCost_14d: Z-Score of the item TotalCost in relation to the distribution of item TotalCost among all items with the same customer_x_product as that item over a 14d period.

ITEM_TotalCost_to_CUSTOMER_X_PRODUCT_item_TotalCost_ratio_14d: Ratio of item TotalCost to the total sum of item TotalCost among all items with the same customer_x_product as that item over the 14d period.

ITEM_TotalCost_Z_Score_to_OVERALL_item_TotalCost_14d: Z-Score of the item TotalCost in relation to the distribution of item TotalCost among all items over a 14d period.

ITEM_Discount_Z_Score_to_PRODUCT_item_Discount_14d: Z-Score of the item Discount in relation to the distribution of item Discount among all items with the same product as that item over a 14d period.

ITEM_Discount_to_PRODUCT_item_Discount_ratio_14d: Ratio of item Discount to the total sum of item Discount among all items with the same product as that item over the 14d period.

ITEM_Discount_Z_Score_to_PRODUCTGROUP_item_Discount_14d: Z-Score of the item Discount in relation to the distribution of item Discount among all items with the same productgroup as that item over a 14d period.

ITEM_Discount_Z_Score_to_CUSTOMER_item_Discount_14d: Z-Score of the item Discount in relation to the distribution of item Discount among all items with the same customer as that item over a 14d period.

ITEM_Discount_to_CUSTOMER_item_Discount_ratio_14d: Ratio of item Discount to the total sum of item Discount among all items with the same customer as that item over the 14d period.

ITEM_Discount_Z_Score_to_CUSTOMER_X_PRODUCT_item_Discount_14d: Z-Score of the item Discount in relation to the distribution of item Discount among all items with the same customer_x_product as that item over a 14d period.

ITEM_Discount_to_CUSTOMER_X_PRODUCT_item_Discount_ratio_14d: Ratio of item Discount to the total sum of item Discount among all items with the same customer_x_product as that item over the 14d period.

ITEM_Discount_Z_Score_to_OVERALL_item_Discount_14d: Z-Score of the item Discount in relation to the distribution of item Discount among all items over a 14d period.

Item Signal type: Attribute stats

ITEM_Discount_to_INVOICE_item_Discount_ratio: Ratio of item Discount to the total sum of item Discount among all items with the same invoice as that item.

Explore features for the Invoice entity

Invoice Signal type: Attribute

INVOICE_Amount: Amount of the invoice

Invoice Signal type: Timing

INVOICE_Hour: Hour of invoice

INVOICE_Weekday: Weekday of invoice

INVOICE_Day: Day of invoice

INVOICE_Week: Week of invoice

INVOICE_Month: Month of invoice

INVOICE_Quarter: Quarter of invoice

Invoice Signal type: Stats

INVOICE_Count_of_item: Count item for the invoice

INVOICE_Sum_of_item_Discount: Sum of item Discount for the invoice.

Invoice Signal type: Diversity

INVOICE_Variability_of_product_ProductGroup_based_on_item_TotalCost: The feature evaluates the distribution of a invoice's item's TotalCost across various product's ProductGroup categories using entropy. Higher entropy signifies a more uniform distribution of item's TotalCost across categories, while lower entropy suggests a concentration within specific product's ProductGroup categories.

INVOICE_Unique_Count_of_product_ProductGroup: Unique Count of product ProductGroup for the invoice.

Invoice Signal type: Similarity

INVOICE_Amount_Z_Score_to_CUSTOMER_invoice_Amount_14d: Z-Score of the invoice Amount in relation to the distribution of invoice Amount among all invoices with the same customer as that invoice over a 14d period.

INVOICE_Amount_to_CUSTOMER_invoice_Amount_ratio_14d: Ratio of invoice Amount to the total sum of invoice Amount among all invoices with the same customer as that invoice over the 14d period.

INVOICE_Amount_Z_Score_to_OVERALL_invoice_Amount_14d: Z-Score of the invoice Amount in relation to the distribution of invoice Amount among all invoices over a 14d period.

Invoice Signal type: Most frequent

INVOICE_product_ProductGroup_with_Highest_sum_of_item_TotalCost: product ProductGroup with Highest sum of item TotalCost for the invoice.

Invoice Signal type: Bucketing

INVOICE_item_TotalCost_across_product_ProductGroups: Distribution representing the cumulative TotalCost of item, categorized by their respective product's ProductGroup, for the invoice.The result is presented as a dictionary where the ProductGroup serves as the key and its corresponding sum of TotalCost forms the value.