- Random Search  Added n_iters and added TimeSeriesPlit Cross Validation Acceptance (check)
- Deep Learning as LSTM
- Dalex Explainer and Lime Explainer. Waiting for faster machine
- Add more SHAP Graphs. Debug the KernelExplainer for non Trees
- Stacking Models for Regression and Classification
- Global Attributs for classes in each model por explanation of every parameter. Also add pros and cons.
- Add Clustering and PCA
- Add Forecasting
- Classification Analysis for multiclass (check)
- Regression Residuals Analysis (check)
- Holidays include them in library. 
- Indicar bien los argumentos de los modelos. Estableciendo como strings aquellos por default. El resto que puedan
ser tratados.
- Add analysis of result. Like best and worst prediction analysis. From Github Repo. So its  achiveable to obtain the correct features analysis of the data.




