LEAST SQUARES APPROACH TO LOCALLY WEIGHTED NAIVE BAYES METHOD

Least Squares Approach to Locally Weighted Naive Bayes Method

This study proposes a new approach which calculates the weights of Locally Weighted lift master csl24ul Naive Bayes (LWNB) developed on Naive Bayes (NB) which is known with its simple structure.In this approach, a new equation is described by assigning a powered weight to each probabilistic factor in classic NB, and it is transformed to a linear fo

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Comparison of Implicit vs. Explicit Regime Identification in Machine Learning Methods for Solar Irradiance Prediction

This work compares the solar power forecasting performance of tree-based methods that include implicit regime-based models to explicit regime separation methods that utilize both unsupervised and supervised machine learning techniques.Previous studies have shown an improvement utilizing a regime-based machine learning approach in a climate with div

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