Logistic Regression Demo with Squid Consultancy Group

Explore our randomly generated dataset or upload your own CSV/XLSX file to perform logistic regression. Select two numeric features, one binary target, and a scaling method to model behavior, view metrics, confusion matrix, decision boundaries, and ROC metrics.

Select Dataset

Upload CSV/XLSX

Feature 1

Feature 2

Target

Feature Scaling Method

Train Split (%): 80

Enable Subsampling

Dataset Preview

Top 5 Rows

Bottom 5 Rows

Dataset Statistics

Model Metrics

Training Set

Accuracy

Precision

Recall

F1 Score

Test Set

Accuracy

Precision

Recall

F1 Score

Confusion Matrix (Test Set)

Decision Boundary (Training Set)

Decision Boundary (Test Set)

ROC Metrics (Test Set)

Area Under Curve (AUC)

Threshold	False Positive Rate (FPR)	True Positive Rate (TPR)