Other pages from this class
Normalisation
- https://en.wikipedia.org/wiki/Feature_scaling
- https://en.wikipedia.org/wiki/Normalization_(statistics)
- min-max
- max-abs
- z-score: results can be ok-ish for most data
- normalização robusta: good if a lot of outliners
- Decimal Scaling Noramlization: all elements will be smaller than 1
- tangent hiberbólica: from -1 to 1
Normality test
- https://en.wikipedia.org/wiki/Normality_test
- Shapiro-Wilk
- Cramér-von Mises (
library(nortest)) - Kolmogorov-Smirnov
- Andreson-Darling
Transform categories in numbers
Evaluation
- https://arjun-mota.github.io/posts/mean-absolute-error/
- https://www.freecodecamp.org/news/machine-learning-mean-squared-error-regression-line-c7dde9a26b93/
- https://en.wikipedia.org/wiki/Coefficient_of_determination
Techniques
- https://en.wikipedia.org/wiki/Cross-validation_(statistics)
- https://pt.wikipedia.org/wiki/Validação_cruzada
- https://www.datarobot.com/wiki/training-validation-holdout/
Metrics
- https://en.wikipedia.org/wiki/Confusion_matrix
- https://en.wikipedia.org/wiki/Receiver_operating_characteristic
- https://en.wikipedia.org/wiki/F-score
Outliers
- https://en.wikipedia.org/wiki/Grubbs's_test
- https://www.rdocumentation.org/packages/EnvStats/versions/2.3.1/topics/rosnerTest
- https://en.wikipedia.org/wiki/Local_outlier_factor
Confusion Matrix
- https://en.wikipedia.org/wiki/Confusion_matrix
- https://en.wikipedia.org/wiki/Receiver_operating_characteristic