MLAI/Classification
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Decision TreeMLAI/Classification 2020. 1. 21. 16:55
1. Overview A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strateg..
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Kernel SVMMLAI/Classification 2020. 1. 21. 00:20
1. Overview 2. Description 2.1 Motivation This happens because in this case the data is not linearly set separable. 2.2 Mapping to a Higher Dimension And now what we want to do is we just want to see that it is indeed linearly separable. And as you can see this dataset became linearly separable in this dimension. It is possible to do the same thing applies to two-dimensional space moving into th..
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Support Vector Machine (SVM)MLAI/Classification 2020. 1. 20. 21:58
1. Overview 2. Description 2.1 Components The line that separates these two classes of points. And at the same time, it has the maximum margin which means this distance so this line is drawn equidistant. And that's margin's So the sum of these two distances has to be maximized in order for this line to be the result of the SVM. And these two points are actually called the support vectors. So bas..
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K-Nearest Neighbors (KNN)MLAI/Classification 2020. 1. 20. 20:49
1. Overview K nearest neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions) 2. Description 2.1 Procedure Step 1: Choose the number K of neighbors Step 2: Take the K nearest neighbors of the new data point, according to the Euclidean distance Step 3: Among these K neighbors, count the number of data points..
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Naive Bayes classifierMLAI/Classification 2019. 10. 6. 18:09
1. Overview 2. Bayes Theorem 2.1 Formula $$P(A|B)=\frac{P(B|A)\times P(A)}{P(B)}$$ 2.2 Example 3. Classifier 3.1 Procedure 3.1.1 Step 1 3.1.2 Step 2 3.1.3 Step 3 The first time we're going to apply it to find out what is the probability that this person walks given his features and X over here is the features or presents the features of that data point. And then we're going to look at all the po..
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Hidden Markov Model(HMM)MLAI/Classification 2019. 10. 4. 21:47
1. Overview HMM is called hidden because only the symbols emitted by the system are observable, not the underlying random walk between states. An HMM can be visualized as a finite state machine. it generates a protein sequence by emitting amino acids as it progresses through a series of states. 2. Description 2.1 Definition of Markov Model There are four common Markov models used in different si..