Naive Bayes classification is a supervised learning algorithm used in the field of machine learning for data classification. It is based on Bayes' theorem and assumes that all input variables are independent of each other.
In simple terms, the algorithm calculates the probability that an input belongs to each possible class, and selects the class with the highest probability as the final classification.
The "Naive" in its name refers to the assumption of independence of the input variables, which may not be true in practice. Despite this simplifying assumption, Naive Bayes classification is widely used due to its ease of implementation and its ability to handle large data sets with high dimensionality.
OpenAI is a technology company created by the main leaders in artificial intelligence that, in its beginnings, defined itself as an organization that [...]
Read More »In recent years, all topics related to Artificial Intelligence (AI) have been arousing enormous interest. Perhaps it is because the heart of [...]
Read More »Artificial intelligence is increasingly present in companies and its growth is being applied in practically all sectors. When the end [...]
Read More »Credit scoring is a system used to rate credits and thus try to automate the decision making process at the time of purchasing a loan, and to [...]
Read More »
