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Abstract: The Random Forest algorithm generates quite diverse decision trees as the base classifiers by applying the Random Subspace algorithm on the bootstrap samples for high dimensional datasets.
To do so, the Probabilistic Random Forest (PRF) algorithm treats the features and labels as probability distribution functions, rather than deterministic quantities. The details of the algorithm along ...
Due to the imbalanced distribution of business data, missing user features, and many other reasons, directly using big data techniques on realistic business data tends to deviate from the business ...
Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.