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Choosing the right linkage method for hierarchical clustering

Methods overview Short reference about some linkage methods of hierarchical agglomerative cluster analysis (HAC). Basic version of HAC algorithm is one generic; it amounts to updating, at each step, ...
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How can an artificial neural network ANN, be used for unsupervised clustering?

Neural networks are widely used in unsupervised learning in order to learn better representations of the input data. For example, given a set of text documents, NN can learn a mapping from document to ...
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Are all Machine Learning algorithms divided into Classification and Regression, not just supervised learning?

No, it's much broader than that. You should at least read about the following: Clustering Dimensionality Reduction Reinforcement Learning
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Distinguishing between two groups in statistics and machine learning: hypothesis test vs. classification vs. clustering

Not going to address clustering because it's been addressed in other answers, but: In general, the problem of testing whether two samples are meaningfully different is known as two-sample testing. ...
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Why use a Gaussian mixture model?

I'll borrow the notation from (1), which describes GMMs quite nicely in my opinon. Suppose we have a feature $X \in \mathbb{R}^d$. To model the distribution of $X$ we can fit a GMM of the form f(...
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Is there any difference between distant supervision, self-training, self-supervised learning, and weak supervision?

There are two aspects to all the different terms you have given: 1] Process of obtaining training data 2] Algorithm that trains $f$ or the classifier The algorithm that trains $f$, regardless of how ...
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t-SNE with mixed continuous and binary variables

Disclaimer: I only have tangential knowledge on the topic, but since no one else answered, I will give it a try Distance is important Any dimensionality reduction technique based on distances (tSNE, ...
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What is the minimum number of data points required for kernel density estimation?

In the book "Density Estimation for Statistics and Data Analysis, Bernard. W. Silverman, CRC ,1986" there is a chapter "Required sample size for given accuracy" where a sample size required is given ...
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In convolutional neural network, what does fully-connected layer mean?

Every neuron from the previous layer is connected to every neuron on the next layer1.
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