Sklearn XGBoost Classifier

XGBoost Classifier is an optimized gradient boosting algorithm that uses ensemble of decision trees. It is designed for efficiency, flexibility, and portability. Provides parallel tree boosting and is widely used for supervised learning tasks like classification.

Type

ml-estimator

Class

fire.nodes.sklearn.NodeXGBoostClassifier

Fields

Name

Title

Description

targetCol

Target Column

The label column for model fitting

featureCols

Feature Columns

Feature columns of type - all numeric, boolean and vector

splitRatio

Split Ratio

Split Ratio

n_estimators

NEstimators

Number of boosting rounds (trees) to fit.

max_depth

MaxDepth

Maximum depth of a tree. Increasing depth makes the model more complex and likely to overfit.

learning_rate

LearningRate

Step size shrinkage used to prevent overfitting. Also called eta.

subsample

Subsample

The fraction of samples used for fitting the individual base learners. Lower values help prevent overfitting.

colsample_bytree

ColsampleByTree

Subsample ratio of columns when constructing each tree.

gamma

Gamma

Minimum loss reduction required to make a further partition on a leaf node.

min_child_weight

MinChildWeight

Minimum sum of instance weight (hessian) needed in a child.

objective

Objective

Specifies the learning task and objective function.

eval_metric

EvalMetric

Evaluation metric for validation data.

reg_alpha

RegAlpha (L1)

L1 regularization term on weights.

reg_lambda

RegLambda (L2)

L2 regularization term on weights.

random_state

RandomState

Random seed for reproducibility.

n_jobs

NJobs

Number of parallel threads used to run xgboost.

confusionMatrix

Confusion Matrix

output_confusion_matrix_chart

Output Confusion Matrix Chart

Whether to display confusion matrix chart.

cm_chart_title

Confusion Matrix Chart Title

Title name to display in Confusion Matrix Chart

cm_chart_description

Confusion Matrix Chart Description

Description to display in Confusion Matrix Chart

confusionMatrixTargetLegend

Confusion Matrix Target Legend

Legend name to display for Target in Confusion Matrix

confusionMatrixPredictedLabelLegend

Confusion Matrix PredictedLabel Legend

Legend name to display for Predicted Label in Confusion Matrix

confusionMatrixCountLegend

Confusion Matrix Count Legend

Legend name to display for Count in Confusion Matrix

path

Save Confusion Matrix Path

Save Confusion Matrix

Description

Confusion Matrix Description

confusionMatrixRowDescription

Confusion Matrix Outcome description

One can provide the business details of the outcome of the confusion matrix rows

ROC Curve

ROC Curve

output_roc_curve

Output ROC Curve

Whether to display ROC Curve chart.

roc_title

ROC Curve Chart Title

Title name to display in ROC Curve Chart

roc_description

ROC Curve Chart Description

Add Description for ROC Curve Chart

xlabel

X Label

X label

ylabel

Y Label

Y label