The goodness of slits is evaluated in gain terms fitting Linear Models in the nodes. This implies that the models in the leaves are linear instead of constant approximations like in classical Decision ...

So, we added each data transformation step (e.g. bag-of-word, TF-IDF, SVC) and classifier (e.g. Naive Bayesian, SVM, Random Forest Classifier) into an instance of class Pipeline. After applying those ...

The use of random forests Classification in medical decision support for diagnosing diseases is investigated in this study. Based on interpretivism, the study uses a design that is descriptive in ...

Early detection of lung cancer through risk factor analysis can significantly improve outcomes. This study presents a novel machine learning approach to analyze risk factors and predict lung cancer ...

Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively ...