A tag is a keyword or label that categorizes your question with other, similar questions. Using the right tags makes it easier for others to find and answer your question.
the process of using domain knowledge of the data to create features that improve machine learning algorithms
Refers to general procedures that attempt to determine the generalizability of a statistical result. Cross-validation arises frequently in the context of assessing how a particular model fit predicts …
a set of one or more computations that will produce a calculated result. All statistics methods are algorithms. Algorithms can be simple, such as calculating a percentage, or can be ve…
a subfield of computer science which deals with analyzing and understanding images. This includes detection of objects like faces in images or segmenting images.
In statistics this refers to selecting an estimator of a parameter by maximizing or minimizing some function of the data. One very common example is choosing an estimator which maximizes the joint den…
Variables (used for prediction or explication) used in regression or regression-like models (like clustering, discrimination). Use this tag for questions about constructing such variables or selecting…
a family of cluster analysis methods in which you specify the number of clusters you expect. This is as opposed to hierarchical cluster analysis methods.
Finding hidden (statistical) structure in unlabelled data, including clustering and feature extraction for dimensionality reduction.
quantify the difference between observed data and predicted values according to a model. Minimization of loss functions is a way to estimate the parameters of the model.
an algorithm for finding the minimum of a function. It iteratively calculates partial derivatives (gradients) of the function and descends in steps proportional to those partial d…
a two layer neural network to process text. It takes words as an input and outputs a vector correspondingly. It uses a combination of Continuous Bag of Word and skipgram model implementati…
the collective name for a set of language modeling and feature learning techniques in NLP where words are mapped to vectors of real numbers in a low dimensional space, relative to th…
a type of machine learning algorithm that learns a mapping function y = f(x) between input variables (x) and output variables (y). The two most common supervised learning tasks …
Categorical data can take on a limited (usually fixed) number of possible values called categories. Categorical values "label", they do not "measure". Nominal and dichotomous/binary scale types are ca…
an open source library for Tensors and Dynamic neural networks in Python with strong GPU acceleration. For details, see https://pytorch.org.
an open source cluster computing system that aims to make data analytics fast — both fast to run and fast to write, originally developed in the AMPLab at UC Berkeley.
Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behaviour. This is also known as outlier detection.
For use when discussing the commutative and linear, but not associative operator interpreted on functions and distributions.
A measure of the degree of linear association among a pair of variables.
Use for questions about Backpropagation, which is commonly used in training Neural Networks in conjunction with an optimization method such as gradient descent.
Use for questions about Orange, the free, open-source, component-based, data mining and machine learning software suite.
Principal component analysis, a technique for dimensionality reduction.
a type of neural network that learns a useful encoding for data.
A form of signal processing where the input is an image. Usually treating the digital image as a two-dimensional signal (or multidimensional). This processing may include image restoration and enhance…
Multilabel classification assigns to each sample a set of target labels. This can be thought as predicting properties of a data-point that are not mutually exclusive, such as topics that are relevant …
a scientific and numerical computing extension to the Python programming language.