Model Generation

Creative, amazing, awesome and unique


Model Evaluation

ML model performance metric

On your most recent evaluation. ev-3fF6uP2W5VL, the ML model's quality score is considered extremely good for most machine learing.

AUC:0.94

Baseline AUC: 0.50

Difference : 0.44


Next Step: If you want to use this ML model to generate predicitions, explore trade-offss to optimize the performance of your ML model first.

Score threshold: 0.5

Model Summary

Model Evalution: Metric Functions

You can use the "Metrics" fuctions to evaluate the accuracy of your model's predictions.

metrics.accuracy_score

metrics.average_precision_score

metrics.metrics.adjusted_rand_score

metrics.mean_absolute_error

metrics.mean_squared_error

metrics.median_absolute_error

Project Summary

Project name Project 1
Data name Data
Domain name Marketing
Anlysis engine Binary Classification
No. of classes 2
No. of input features 195
No. of records 3178