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Model's k-fold cross-validation | BigML.com
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Model's k-fold cross-validation
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Created
Thu, 8 Oct 2026 14:59:00 +0000
Published
Thu, 8 Oct 2026 17:26:38 +0000
Description:
k-fold cross-validation for models
Tags:
BigMLer
BigMLer_ThuOct0826_165856
fold cross
URL:
https://bigml.com/user/whizzml/gallery/script/6ac7afb412163ebf324fb4dc
Script
FREE
Source code
;; This code will eventually be defined as a library. ;;get-model-options ;; ;; maps the options to be used in models ;; Inputs: ;; missing-splits: (boolean) Sets the missing_splits flag ;; stat-pruning: (boolean) Sets the statistical pruning flag ;; balance-objective: (boolean) Sets the balance_objective flag ;; weight-field: (string) ID of the field to be used as weight (weight_field) ;; objetive-weights: (list) List of values to be used as objective_weights ;; node-threshold: (integer) maximum number of nodes in the model ;; ;; Output: (map) options map ;; (define (get-model-options missing-splits pruning balance-objective weight-field objetive-weights node-threshold) (let (options {"missing_splits" missing-splits "stat_pruning" stat-pruning "balance_objective" balance-objective} options (if (empty? weight-field) options (assoc options "weight_field" weight-field)) options (if (empty? objective-weights) options (assoc options "objective_weights" objective-weights))) (if (= node-threshold -1) options (assoc options "node_threshold" node-threshold)))) ;; model-cross-validation ;; ;; creates k-fold cross-validation for a dataset using models ;; ;; Inputs: ;; dataset-id: (string) Dataset ID ;; k-folds: (integer) Number of folds ;; objective-id: (string) ID of the objective field ;; missing-splits: (boolean) sets the missing_splits flag ;; pruning: (string) pruning configuration option ;; balance-objective: (boolean) sets the balance_objective flag ;; weight-field: (string) ID of the field to be used as weight_field ;; objective-weights: (list) List of objective_weights ;; node-threshold: (integer) maximum number of nodes in the model ;; delete-resources?: (boolean) Whether to delete all intermediate resources ;; stratified?: (boolean) Whether to stratify the k-folds across classes ;; ;; Output: (evaluation-id) Average of evaluations results ;; (define (model-cross-validation dataset-id k-folds objective-id missing-splits stat-pruning balance-objective weight-field objective-weights node-threshold delete-resources? . stratified?) (let (options (get-model-options missing-splits stat-pruning balance-objective weight-field objective-weights node-threshold) objective-id (if (empty? objective-id) (dataset-get-objective-id dataset-id) objective-id) dft-evaluation-options {}) (ds-cross-validation dataset-id k-folds objective-id "model" options dft-evaluation-options delete-resources? stratified?))) (define cross-validation-output (model-cross-validation dataset-id k-folds objective-id missing-splits stat-pruning balance-objective weight-field objective-weights node-threshold delete-resources? stratified?))
Description
k-fold cross-validation for models
k-fold cross-validation for models
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License:
Creative Commons Zero V1.0
Script
FREE
Model's k-fold cross-validation | BigML.com
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