Which type of data is Naive Bayes particularly good at handling?Answer areaContinuous dataText dataImage dataTime-series data

Naive Bayes is particularly good at handling text data. This is primarily because it is designed to work with categorical data and can effectively apply the Bayes theorem in classification tasks, particularly for tasks like spam detection, sentiment analysis, and document classification. Text data can be converted into a suitable format for Naive Bayes through techniques like bag-of-words or term frequency-inverse document frequency (TF-IDF), allowing the algorithm to efficiently calculate probabilities of classes based on the presence of words. Therefore, it excels in scenarios involving large amounts of textual information where the independence assumption holds fairly well.