a learning algorithm ... the problem a regression problem if instead the output values are a small set of values (like ham/spam, or sunny/cloudy/rainy), then we call it a classification problem there ...

Examples of supervised learning algorithms are Linear Regression, Logistic Regression, K-nearest Neighbors, Decision Trees, and Support Vector Machines. Meanwhile, some examples of unsupervised ...

Linear regression algorithms fit a straight ... there are another two kinds of machine learning algorithms: supervised and unsupervised. In supervised learning, you provide a training data set ...

Margaret Rouse is an award-winning technical writer and teacher known for her ability to explain complex technical subjects simply to a non-technical, business audience. Over… Supervised learning ...

Regression algorithms fall under the family of Supervised Machine Learning algorithms which is a subset of machine learning algorithms. One of the main features of supervised learning algorithms is ...

Supervised learning and unsupervised learning ... Listing 3 shows Java code for the gradient descent algorithm. The thetas of the regression function will be trained using the training data ...

Abstract: Semi-supervised learning (SSL), which can exploit both labeled ... The proposed method uses belief functions to address the uncertainty in the semi-supervised regression. The algorithm uses ...