deep learning prediction -- 2

Prediction using 4 deep learning methods for different attributes for 3 datasets. show the test and train results so no overfitting or underfitting.
results from the table show results of prediction comparing 7 results
Then predict it shows the prediction using all attributes then the prediction using 9 kano features ( (7, 13, 25, 27, 35, 12, 23, 31,36) then 9 features from each feature selection then the prediction common features then predcition union features
Method Feature Selected then Common Variables
Chi-Square 34,37,27,35,18,16,13,7,2 common 27, 35, 13, 7
Mutual Information Gender,20,27,23,16,29,21,17,9 common 27, 23
Lasso 27,2,37,7,36,34,6,21,35 common 27, 7, 36, 35
ANOVA 2,7,13,16,21,23,27,32,34 common 7, 13, 35, 27
Pearson 27,34,2,7,37,32,16,21,35 common 27, 7, 35

Ada Boost Regression(depth=15) Tree Model R_Square RMSE MAE Pearson's Correlation Coefficient
0 ALL
1 kano
2 Anova
3 Chi-Square
4 Lasso
5 Mutual information
6 Pearson
then union
Method Feature Selected Union Variables
Chi-Square 34,37,27,35,18,16,13,7,2 union 34,37,18,16,2,7,13,25,27,35,12,23,31,36
Mutual Information Gender,20,27,23,16,29,21,17,9 union G,20,16,29,21,17,9,7,13,25,27,35,12,23,31,36
Lasso 27,2,37,7,36,34,6,21,35 union 2,37,34,6,21,7,13,25,27,35,12,23,31,36
ANOVA 2,7,13,16,21,23,27,32,34 union 2,16,21,32,34,7,13,25,27,35,12,23,31,36
Pearson 27,34,2,7,37,32,16,21,35,6 union 34,2,37,32,16,21,7,13,25,27,35,12,23,31,36