I have generated 42 features from the existing dataset for a prediction task. All these features are significantly correlated with the target variable (ranging from .25 to .05). For the dimension reduction I used PCA. However, when I run the linear regression model I obtain a very low r2 value (~0.057). At this point I don't know what to do and how to proceed. I am thinking to generate more sparse feature set to improve the prediction. Any recommendations? I appreciate any help.