Heart disease is a leading cause of death worldwide, and the need for effective predictive systems major source to treat affected patients. This study aimed determine how improve accuracy Random Forest in predicting classifying heart disease. The experiments performed this were designed select most optimal parameters using an RF optimization technique GA. Genetic Algorithm (GA) used optimize pr...

To address the contextual bandit problem, we propose an online random forest algorithm. The analysis of the proposed algorithm is based on the sample complexity needed to find the optimal decision stump. Then, the decision stumps are recursively stacked in a random collection of decision trees, BANDIT FOREST. We show that the proposed algorithm is optimal up to logarithmic factors. The dependen...

As society has developed, increasing amounts of data have been generated by various industries. The random forest algorithm, as a classification is widely used because its superior performance. However, the algorithm uses simple sampling feature selection method when generating subspaces which cannot distinguish redundant features, thereby affecting accuracy, and resulting in low calculation ef...

Retaining customers is becoming a measurement focus in an industry with increasing competition. The concept of customer retention has become research study the sales industry, because it difficult to retain and easily switch other brands. Customer repurchase decisions business world are very competitive. satisfaction directly proportional rate, if not satisfied then automatic rate will be low. ...

In order to further improve the identification efficiency of tobacco mildew, a rapid model mildew based on random forest algorithm was proposed in this study. ensure feasibility and pertinence study, study takes redried leaf as research object, selects high-temperature high-humidity environment experimental conditions, obtains sample data degree under different conditions. At same time, paper c...

Abstract Network security is subject to malicious attacks from multiple sources, and intrusion detection systems play a key role in maintaining network security. During the training of models, results generally have relatively large false rates due shortage data caused by imbalance. To address existing sample imbalance problem, this paper proposes algorithm based on enhanced random forest synth...