codesnips

classification

python 
import numpy as np
from sklearn.metrics import confusion_matrix

probabilities = model.predict_proba(X_valid)[:, 1]
thresholds = np.linspace(0.1, 0.9, 9)

Confusion matrix diagnostics for threshold selection

confusion-matrix thresholding evaluation
by Dr. Elena Vasquez 1 tab
python 
from sklearn.ensemble import RandomForestClassifier, HistGradientBoostingClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import roc_auc_score
from sklearn.pipeline import Pipeline
from sklearn.impute import SimpleImputer

Baseline classifiers in scikit-learn for fast benchmark setting

scikit-learn classification baselines
by Dr. Elena Vasquez 1 tab