<prompt> Naive libes ke eng?nan  <response>: Instruction in English: What is naive bayes? . Response in English: Naive Bayes is a classification algorithm based on Bayes theorem that assumes independence among predictors. It is a probabilistic algorithm, which means that it makes predictions based on the probability of an event happening. The fundamental idea behind Naive Bayes is that the probability of an event happening can be calculated from the frequency of occurrence of related events. This makes it particularly suitable for dealing with categorical variables.In practice, Naive Bayes is often used in text classification, spam filtering, and sentiment analysis. The algorithm is simple to implement, fast and can handle large datasets. However, the assumption of independence among variables may not always hold in real-world scenarios, and this could lead to reduced accuracy in prediction. . Response in Sesotho: Naive Bayes ke algorithm ea mekhahlelo e thehiloeng ho theorem ea Bayes e nkang boipuso hara ba bolelang esale pele. Ke algorithm ea probabilistic, e bolelang hore e etsa likhakanyo ho latela monyetla oa hore ketsahalo e etsahale. Mohopolo oa mantlha ka morao ho Naive Bayes ke hore monyetla oa hore ketsahalo e etsahale o ka baloa ho tloha khafetsa ho etsahala ha liketsahalo tse amanang. Sena se etsa hore e be e loketseng ka ho khetheha bakeng sa ho sebetsana le mefuta e fapaneng ea categorical. Ha e le hantle, Naive Bayes e sebelisoa hangata ho arola mongolo, ho hlopha spam, le tlhahlobo ea maikutlo. Algorithm e bonolo ho e sebelisa, e potlakile ebile e khona ho sebetsana le li-dataset tse kholo. Leha ho le joalo, khopolo ea boipuso hara mefuta e fapaneng e ka na ea se ke ea lula e tšoarella maemong a sebele a lefatse, me sena se ka lebisa ho fokotseng ho nepahala ha ho bolela esale pele. 