5 posts on machine learning. All posts · RSS feed
Classification problems are a broad class of machine learning applications devoted to assigning input data to a predefined category based on its features. If the boundary between the categories has a linear relationship to the input data, a simple logistic regression algorithm may do a …
In the notation of this previous post, a logistic regression binary classification model takes an input feature vector, , and returns a probability, , that belongs to a particular class: . The model is trained on a set of provided example feature vectors, , and …
Simple logistic regression is a statistical method that can be used for binary classification problems. In the context of image processing, this could mean identifying whether a given image belongs to a particular class () or not (), e.g. "cat" or "not cat". A logistic …
The website exoplanets.org hosts a repository of data on over 5000 exoplanets discovered by various missions and techniques. For this post, I have extracted data on the mass and orbital period of 2951 exoplanets: exoplanet-data-160824.csv. The planetary masses are expressed relative to the mass of …
In the gradient descent method of optimization, a hypothesis function, , is fitted to a data set, () by minimizing an associated cost function, in terms of the parameters . The cost function describes how closely the hypothesis fits the data for a given choice …
