Ml Feature Selector

A powerful model routing skill that analyzes query intent and cost-efficiency to select the optimal LLM (Elite/Balanced/Basic) before execution.

Calculates classification and regression metrics like accuracy, F1-score, RMSE, and provides confusion matrix to evaluate ML model performance.

Cleans and preprocesses datasets for ML by imputing missing values, scaling numeric features, and encoding categorical variables.

Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.

Helps choose the right fal.ai model before API calls. Provides quick decision matrix for video generation (text-to-video, image-to-video), image editing (obj...

Automates training of machine learning models like Random Forest and XGBoost with hyperparameter tuning and export options from provided datasets.