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What is HGB?

HistGradientBoosting is a gradient boosting technique that uses histogram-based optimization to efficiently train models on large datasets. It builds models sequentially, with each new model correcting errors made by the previous ones. This method enhances performance while reducing training time and memory usage. HistGradientBoosting is particularly effective in capturing complex data patterns and is often used in scenarios requiring high predictive accuracy.

Most Frequent Parameters

  • early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1 - Count: 5
  • learning_rate: 0.01, max_depth: 7, max_iter: 300 - Count: 2
  • learning_rate: 0.1, max_depth: 3, max_iter: 100 - Count: 2
  • early_stopping: True, l2_regularization: 0, learning_rate: 0.01, max_bins: 255, max_depth: 5, max_iter: 100, min_samples_leaf: 1 - Count: 2
  • early_stopping: True, l2_regularization: 0.1, learning_rate: 0.01, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1 - Count: 1

Average Scores Based on Model History

  • Average Accuracy: 0.91
  • Average Precision: 0.91
  • Average Recall: 0.91
  • Average F1 Score: 0.91

HGB Model History


General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: December 20, 2024, 11:03 p.m.
  • Evaluation Date: December 20, 2024, 11:03 p.m.
  • Popularity History Timeframe: 11/21/2024 - 12/21/2024

Performance Metrics
  • Accuracy: 0.96
  • Precision: 0.96
  • Recall: 0.96
  • F1 Score: 0.96
  • Confusion Matrix: [[ 9, 3, 0], [ 0, 150, 0], [ 0, 4, 8]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: December 13, 2024, 11:03 p.m.
  • Evaluation Date: December 13, 2024, 11:03 p.m.
  • Popularity History Timeframe: 11/14/2024 - 12/14/2024

Performance Metrics
  • Accuracy: 0.96
  • Precision: 0.96
  • Recall: 0.96
  • F1 Score: 0.96
  • Confusion Matrix: [[ 9, 3, 0], [ 0, 150, 0], [ 0, 4, 8]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: December 6, 2024, 11:03 p.m.
  • Evaluation Date: December 6, 2024, 11:03 p.m.
  • Popularity History Timeframe: 11/07/2024 - 12/07/2024

Performance Metrics
  • Accuracy: 0.96
  • Precision: 0.96
  • Recall: 0.96
  • F1 Score: 0.96
  • Confusion Matrix: [[ 9, 3, 0], [ 0, 150, 0], [ 0, 4, 8]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: December 3, 2024, 12:09 p.m.
  • Evaluation Date: December 3, 2024, 12:09 p.m.
  • Popularity History Timeframe: 11/03/2024 - 12/03/2024

Performance Metrics
  • Accuracy: 0.96
  • Precision: 0.96
  • Recall: 0.96
  • F1 Score: 0.96
  • Confusion Matrix: [[ 9, 3, 0], [ 0, 150, 0], [ 0, 4, 8]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.1, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: November 29, 2024, 11:09 p.m.
  • Evaluation Date: November 29, 2024, 11:09 p.m.
  • Popularity History Timeframe: 10/31/2024 - 11/30/2024

Performance Metrics
  • Accuracy: 0.95
  • Precision: 0.95
  • Recall: 0.95
  • F1 Score: 0.95
  • Confusion Matrix: [[ 9, 3, 0], [ 0, 149, 1], [ 0, 4, 8]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0.1, learning_rate: 0.01, max_bins: 255, max_depth: None, max_iter: 100, min_samples_leaf: 1
  • Create Date: November 22, 2024, 11:09 p.m.
  • Evaluation Date: November 22, 2024, 11:09 p.m.
  • Popularity History Timeframe: 10/24/2024 - 11/23/2024

Performance Metrics
  • Accuracy: 0.97
  • Precision: 0.97
  • Recall: 0.97
  • F1 Score: 0.97
  • Confusion Matrix: [[ 5, 2, 0], [ 0, 156, 0], [ 0, 3, 6]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0, learning_rate: 0.01, max_bins: 255, max_depth: 5, max_iter: 100, min_samples_leaf: 1
  • Create Date: October 19, 2024, 3:03 p.m.
  • Evaluation Date: October 19, 2024, 3:03 p.m.
  • Popularity History Timeframe: 09/19/2024 - 10/19/2024

Performance Metrics
  • Accuracy: 0.86
  • Precision: 0.87
  • Recall: 0.86
  • F1 Score: 0.85
  • Confusion Matrix: [[33, 16, 0], [ 1, 98, 1], [ 0, 5, 6]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: early_stopping: True, l2_regularization: 0, learning_rate: 0.01, max_bins: 255, max_depth: 5, max_iter: 100, min_samples_leaf: 1
  • Create Date: October 18, 2024, 1:16 a.m.
  • Evaluation Date: October 18, 2024, 1:16 a.m.
  • Popularity History Timeframe: 09/18/2024 - 10/18/2024

Performance Metrics
  • Accuracy: 0.86
  • Precision: 0.86
  • Recall: 0.86
  • F1 Score: 0.85
  • Confusion Matrix: [[97, 3, 2], [12, 29, 0], [ 6, 0, 11]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: learning_rate: 0.01, max_depth: 7, max_iter: 300
  • Create Date: October 17, 2024, 11:39 p.m.
  • Evaluation Date: October 17, 2024, 11:39 p.m.
  • Popularity History Timeframe: 09/18/2024 - 10/18/2024

Performance Metrics
  • Accuracy: 0.84
  • Precision: 0.84
  • Recall: 0.84
  • F1 Score: 0.84
  • Confusion Matrix: [[97, 4, 1], [12, 27, 2], [ 6, 0, 11]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: learning_rate: 0.1, max_depth: 3, max_iter: 100
  • Create Date: October 17, 2024, 11:31 p.m.
  • Evaluation Date: October 17, 2024, 11:31 p.m.
  • Popularity History Timeframe: 09/18/2024 - 10/18/2024

Performance Metrics
  • Accuracy: 0.93
  • Precision: 0.92
  • Recall: 0.93
  • F1 Score: 0.92
  • Confusion Matrix: [[114, 0, 1], [ 0, 21, 1], [ 10, 0, 13]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: learning_rate: 0.1, max_depth: 3, max_iter: 100
  • Create Date: October 17, 2024, 7:16 p.m.
  • Evaluation Date: October 17, 2024, 7:16 p.m.
  • Popularity History Timeframe: 09/17/2024 - 10/17/2024

Performance Metrics
  • Accuracy: 0.93
  • Precision: 0.92
  • Recall: 0.93
  • F1 Score: 0.92
  • Confusion Matrix: [[114, 0, 1], [ 0, 21, 1], [ 10, 0, 13]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: learning_rate: 0.01, max_depth: 7, max_iter: 300
  • Create Date: October 17, 2024, 5:31 p.m.
  • Evaluation Date: October 17, 2024, 5:31 p.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.88
  • Precision: 0.87
  • Recall: 0.88
  • F1 Score: 0.86
  • Confusion Matrix: [[113, 0, 2], [ 4, 18, 0], [ 13, 1, 9]]

Feature Importance
  • No feature importance data available.

File Downloads

Download CSV Download Model File (pkl) Download README TXT

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: October 16, 2024, 6:38 p.m.
  • Evaluation Date: October 16, 2024, 6:38 p.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.91
  • Precision: 0.90
  • Recall: 0.91
  • F1 Score: 0.90

Feature Importance
  • No feature importance data available.

File Downloads

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: October 13, 2024, 11:22 a.m.
  • Evaluation Date: October 13, 2024, 11:22 a.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.91
  • Precision: 0.90
  • Recall: 0.91
  • F1 Score: 0.90

Feature Importance
  • No feature importance data available.

File Downloads

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: October 9, 2024, 12:31 a.m.
  • Evaluation Date: October 9, 2024, 12:31 a.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.93
  • Precision: 0.94
  • Recall: 0.93
  • F1 Score: 0.92

Feature Importance
  • No feature importance data available.

File Downloads

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: October 7, 2024, 9:54 a.m.
  • Evaluation Date: October 7, 2024, 9:54 a.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.92
  • Precision: 0.91
  • Recall: 0.92
  • F1 Score: 0.91

Feature Importance
  • No feature importance data available.

File Downloads

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: October 1, 2024, 7:31 p.m.
  • Evaluation Date: October 1, 2024, 7:31 p.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.89
  • Precision: 0.90
  • Recall: 0.89
  • F1 Score: 0.88

Feature Importance
  • No feature importance data available.

File Downloads

General Information
  • Model Type: HistGradientBoosting
  • Parameters: None
  • Create Date: September 21, 2024, 7:31 p.m.
  • Evaluation Date: September 21, 2024, 7:31 p.m.
  • Popularity History Timeframe: None

Performance Metrics
  • Accuracy: 0.86
  • Precision: 0.85
  • Recall: 0.86
  • F1 Score: 0.85

Feature Importance
  • No feature importance data available.

File Downloads