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Machine Learning (Model selection and evaluation (Model evaluation:…
Machine Learning
Classification
Supervised learning
Generalized Linear Models
Preprocessing data
StandardScaler
Model selection and evaluation
Cross-validation: evaluation estimator performance
K-fold
If one knows that the samples have been generated using a time-dependent process, it’s safer to use a time-series aware cross-validation scheme
Tuning the hyper-parameters of an estimator
Model evaluation: quantifying the quality of predictions
Classification
Accuracy
Balanced_accuracy
Average precision
Bried score loss
F1
Neg log loss
Recall
ROC, AUC
Clustering
Regression
Model persistence
Validation curves: plotting scores to evaluate models
Data visuazlization
https://plot.ly/
Deloy model
Model analysis
Feature importance