The

number of categorical features is less so one-hot encoding can be effectively

applied

The

categorical feature (X) is nominal

The

number of categories is quite large as one-hot encoding can lead to high memory

consumption

The

categorical feature is ordinal

RMSE

binary_crossentropy

MAE

categorical_crossentropy

MSE

Dropout

Data Augmentation

It is a GPU-accelerated library of primitives for deep neural networks

It implements standard routines such as convolution, pooling,

normalization, and activation layers.

A parallel computing platform including a compiler and a set of development tools created by Nvidia

RNA

Decision Tree

RF

SVM

K-NN

Codificación de datos categóricos

Escalado

y normalización de datos

Imputación de datos

Reducción

de dimensiones

Detección

de atípicos