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
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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 -
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: 1
Average Scores Based on Model History
- Average Accuracy: 0.90
- Average Precision: 0.90
- Average Recall: 0.90
- Average F1 Score: 0.89
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: November 30, 2024, 9:09 a.m.
- Evaluation Date: November 30, 2024, 9:09 a.m.
- Popularity History Timeframe: 10/30/2024 - 11/29/2024
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
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 23, 2024, 9:09 a.m.
- Evaluation Date: November 23, 2024, 9:09 a.m.
- Popularity History Timeframe: 10/23/2024 - 11/22/2024
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
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 20, 2024, 12:03 a.m.
- Evaluation Date: October 20, 2024, 12:03 a.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
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, 10:16 a.m.
- Evaluation Date: October 18, 2024, 10:16 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
General Information
- Model Type: HistGradientBoosting
- Parameters: learning_rate: 0.01, max_depth: 7, max_iter: 300
- Create Date: October 18, 2024, 8:39 a.m.
- Evaluation Date: October 18, 2024, 8:39 a.m.
- Popularity History Timeframe: 09/17/2024 - 10/17/2024
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
General Information
- Model Type: HistGradientBoosting
- Parameters: learning_rate: 0.1, max_depth: 3, max_iter: 100
- Create Date: October 18, 2024, 8:31 a.m.
- Evaluation Date: October 18, 2024, 8:31 a.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
General Information
- Model Type: HistGradientBoosting
- Parameters: learning_rate: 0.1, max_depth: 3, max_iter: 100
- Create Date: October 18, 2024, 4:16 a.m.
- Evaluation Date: October 18, 2024, 4:16 a.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
General Information
- Model Type: HistGradientBoosting
- Parameters: learning_rate: 0.01, max_depth: 7, max_iter: 300
- Create Date: October 18, 2024, 2:31 a.m.
- Evaluation Date: October 18, 2024, 2:31 a.m.
- Popularity History Timeframe: 09/17/2024 - 10/17/2024
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
General Information
- Model Type: HistGradientBoosting
- Parameters:
- Create Date: October 17, 2024, 3:38 a.m.
- Evaluation Date: October 17, 2024, 3:38 a.m.
- Popularity History Timeframe: 09/16/2024 - 10/16/2024
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:
- Create Date: October 13, 2024, 8:22 p.m.
- Evaluation Date: October 13, 2024, 8:22 p.m.
- Popularity History Timeframe: 09/13/2024 - 10/13/2024
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:
- Create Date: October 9, 2024, 9:31 a.m.
- Evaluation Date: October 9, 2024, 9:31 a.m.
- Popularity History Timeframe: 09/09/2024 - 10/09/2024
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:
- Create Date: October 7, 2024, 6:54 p.m.
- Evaluation Date: October 7, 2024, 6:54 p.m.
- Popularity History Timeframe: 09/07/2024 - 10/07/2024
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:
- Create Date: October 2, 2024, 4:31 a.m.
- Evaluation Date: October 2, 2024, 4:31 a.m.
- Popularity History Timeframe: 09/01/2024 - 10/01/2024
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:
- Create Date: September 22, 2024, 4:31 a.m.
- Evaluation Date: September 22, 2024, 4:31 a.m.
- Popularity History Timeframe: 08/22/2024 - 09/21/2024
Performance Metrics
- Accuracy: 0.86
- Precision: 0.85
- Recall: 0.86
- F1 Score: 0.85
Feature Importance
- No feature importance data available.
File Downloads