Add classification and regression metrics

[msluszniak]

I want to add all the existing metrics which are present in Sci-kit Learn.

Classification Metrics

• Accuracy
• AUC
• Average Precision (AP)
• Balanced Accuracy
• Brier Score Loss
• Cohen Kappa Score
• Confusion Matrix
• Discounted Cumulative Gain (DCG)
• Detection Error Tradeoff Curve (DET curve)
• F1 Score
• F-beta Score
• Hamming Loss
• Log Loss
• Matthews correlation coefficient (MCC)
• Normalized Discounted Cumulative Gain (Normalized DCG)
• Precision Recall Curve
• Precision Recall Fscore Support
• Precision
• Recall
• ROC-AUC
• ROC Curve
• Top-k Accuracy Score
• Zero-one Classification Loss

Regression Metrics

• Explained Variance Score
• Maximum Residual Error
• Mean Absolute Error (MAE)
• Mean Squared Error (MSE)
• Mean Squared Log Error
• Mean Absolute Percentage Error (MAPE)
• $R^2$ Score
• Mean Poisson deviance
• Mean Gamma deviance
• Mean Tweedie deviance
• $D^2$ - Fraction of Tweedie Deviance Explained
• Mean Pinball Loss
• $D^2$ - Fraction of Pinball Loss Explained
• $D^2$ - Fraction of Absolute Error Explained

We can do the same for distances after (look #149).

[paulsullivanjr]

I'd like to contribute to this project. I will start working on a PR for "Discounted Cumulative Gain (DCG)"

[msluszniak]

I'd like to contribute to this project. I will start working on a PR for "Discounted Cumulative Gain (DCG)"

Really cool! Feel free to go :)

[paulsullivanjr]

I have Normalized DCG in progress.

[JoaquinIglesiasTurina]

I have mean pinball loss in progress.

[srzeszut]

I am working with @ksew1 and @norm4nn on the remaining metrics.

[msluszniak]

We added all metrics, thank all of you who contributed ❤️