statisticallearned
statisticallearned refers to a set of machine learning techniques that rely heavily on statistical principles to learn patterns from data. These methods assume that data is generated from an underlying statistical distribution, and the goal is to estimate this distribution or use it to make predictions. Common examples of statistical learning methods include linear regression, logistic regression, Naive Bayes, and support vector machines.
The core idea behind statistical learning is to build a model that can generalize well to unseen
Statistical learning methods can be broadly categorized into supervised learning, where the model learns from labeled
The success of statistical learning depends on various factors, including the quality and quantity of the data,