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Category Archives: Machine Learning
Questions on K means method
What is K means algorithm? What is the optimization function? The partial derivative of Distortion J with respect to each center location must be zero. Will the algorithm stop? When J is minimized, (1) each is encoded by its nearest center … Continue reading
Posted in Machine Learning
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SVM notes
Support vector machine can be used for classification and regression. It has successful applications in many fields, like bioinformatics, text, image recognition, etc. Its main ideas are large margin and kernel trick. Margins: 1.Intuition To make things easier, we suppose … Continue reading
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A brief introduction to Neural Networks with an example in R
Motivation: Suppose there are two predictors and the decision boundary is non-linear, then one can introduce quadratic terms in the logistic regression, i.e. $ latex h_{\theta}(x)=g(\theta_0+\theta_1 x_1+\theta_3 x_2+\theta_4 x_1^2+\theta_5 x_1x_2+\theta_6 x_2^2),$ where is the logistic function. However, most questions have more … Continue reading
Posted in Machine Learning, R
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Recommender Systems （Notes from Mining of Massive Datasets ）
What is Recommender Systems (RS)? It is a subclass of information filtering systems that are meant to predict the preferences or ratings that a user would give to a product. Recommender systems are widely used in movies, news, research articles, … Continue reading
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Classification
There are many classifiers to predict a qualitative response (categorical): logistic regression, linear discriminant analysis, KNN, trees, random forests, boosting support vector machines and so on. Why classification? (1)When it is binary qualitative response, we can code the two … Continue reading
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Perplexity is the beginning of knowledge 