Enhances Competitive Advantage:Heatmaps can help us to study the competitive landscape of the market. Businesses can identify the scope to increase their sales in respective competitors’ locations by using numerical data in heatmaps. The Best Practices of Heatmap Select the right color palette: T...
Specifically, you can change the fontsize parameter in the heatmap function call on line 74. The default value is 14; you can increase it to the desired size. However, please note that while increasing the font size may make the numbers in the plot more readable, it may also reduce the...
conf_matrix = metrics_dict["Confusion Matrix"] ax= plt.subplot() sns.heatmap(conf_matrix, annot=True, ax = ax, cmap ='Blues');#annot=True to annotate cells# labels, title and ticksax.set_xlabel('Predicted labels');ax.set_ylabel('True labels'); ax.set_title('Confusion Matrix'); ...
The best parameters for the forest model according to the grid search we defined include the mean absolute error criterion, a minimum leaf sample size of three and 80 estimators (trees). With these settings we can again — compared to the single decision tree — increase the training accuracy ...
_results_['mean_test_score'],'weight': (1- weights)}) sns.lineplot(weigh_data['weight'], weigh_data['score']) plt.xlabel('Weight for class 1') plt.ylabel('F1 score') plt.xticks([round(i/10,1)foriinrange(0,11,1)]) plt.title('Scoring for different class weights', fontsize=...