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Logistic regression is one of the popular approaches for classification, in which a type of regression analysis is used for predicting the outcome of a cat- egorical criterion variable based on one or more predictor variables.
In this paper, we propose Logistic Tensor Regression (LTR) for classification of high-dimensional data with structural information. The proposed LTR not only ...
In this paper, we propose Logistic Tensor Regression (LTR) for classification of high-dimensional data with structural information. The proposed LTR not only ...
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Can I use logistic regression for classification?
Why is logistic regression called regression but still used for classification problems?
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Aug 15, 2024 · This guide demonstrates how to use the TensorFlow Core low-level APIs to perform binary classification with logistic regression.
A new matrix-based regression algorithm for classification, in which the input matrices to be classified are directly used to learn two regression matrices ...
Jul 9, 2024 · Logistic regression is a popular statistical method used for binary classification problems. It models the probability that a given input belongs to a ...
Feb 8, 2024 · Logistic regression is a classification technique that identifies the best fitting model to describe the relationship between the dependent and independent ...
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Jun 20, 2024 · Logistic regression is a supervised machine learning algorithm used for classification tasks where the goal is to predict the probability that an instance ...
Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in ...
In this paper, we propose Logistic Tensor Regression (LTR) for classification of high-dimensional data with structural information. The proposed LTR not only ...