随笔分类 - 机器学习笔记
PRML学习过程中的一些公式推导及程序实现
摘要：The central idea is to extract linear combinations of the inputs as derived features, and then model the target as a nonlinear function of these featu
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摘要：Suppose that we model each class density as multivariate Gaussian, in practice we do not know the parameters of the Gaussian distributions, and will n
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摘要：The hidden neurons act as feature detectors; as such, they play a critical role in the operation of a multiplayer perceptron. As the learning process
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摘要：#include <iostream> #include <sstream> #include <fstream> #include <algorithm> #include <vector> void Conv(std::vector<std::vector<int> > &vv_image, s
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摘要：import pandas as pd import numpy as np import math data = pd.read_csv('c:\\housing.csv') room_nums = data['total_rooms'].tolist() room_mean = np.mean(
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摘要：#include <iostream>#include <vector>#include <cmath>#include <algorithm>#include <numeric>#include <fstream>#include <sstream>#include <functional> do
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摘要：#include <iostream> #include <vector> #include <cmath> #include <algorithm> #include <numeric> double myfunction(double num) { return exp(num); } temp
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摘要：If we compare this to the LMS update rule, we see that it looks identical; but this is not the same algorithm, because h(x) is now defined as a none-l
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摘要：Under the previous probabilistic assumptions on the data, least-squares regression corresponds to finding the maximum likelihood estimate of θ. This i
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摘要：The learning algorithm has the property that it can modify its input/output relationship f-hat in response to differences yi-f(xi)-hat between the ori
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摘要：Most statistical approaches to outlier detection are based on building a probability distribution model and considering how likely objects are under t
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摘要：#include <iostream> #include <vector> #include <cstddef> #include <string> #include <sstream> #include <fstream> #include <algorithm> #include <cmath>
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摘要：template <class T> double VectorMedian(std::vector<T> &In) { std::sort(In.begin(), In.end()); if(In.size() % 2 == 0) { return 0.5*(In.at(In.size()/2)+
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摘要：Many linear parametric models can be re-cast into an equivalent 'dual representstion' in which the predictions are also based on linear combinations o
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摘要：Newton's method is primarily a method for finding the zeros of a function, say f(w), that is, a method for finding solutions to the equation f(w)=0. T
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