Machine Learning, Linear Regression, Ridge Regression, Lasso Regression, Genomics.
search.fit(X.iloc[:, 0:100], y) # summarize print('MAE: %.3f' % results.best_score_) print('Config: %s' % results.best_params_) Let’s try these parameters and make a plot. from sklearn.linear_model import ElasticNet model = ElasticNet(alpha=0.01, l1_ratio=0.03) model.fit(X_train.iloc[:, 0:100],