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    發布日期: 2023-11-15
  • 語言: 其他
  • 標簽: 十大算法??

資源簡介

機器學習十大算法C實現 每種算一個文本 親測有效可用

資源截圖

代碼片段和文件信息 

#include
#include?
#include?
#include?
#include?
#include?
#include?“matrix.h“

using?namespace?std;

#define?MAX?1000000
#define?MIN?-100000

struct?Stump?{
	mapstumpDim;
	mapstumpThresh;
	mapstumpIneq;
	mapstumpAlpha;
};

vectorweakClassArr;


//求每列的最大最小
void?rangeSize（Matrix?&Data?int?&axis?vector?&rangeVal）
{
	rangeVal.clear（）;
	rangeVal.push_back（MIN）;
	rangeVal.push_back（MAX）;
	for?（int?i?=?0;?i?	{
		if?（Data.mat[i][axis]>rangeVal[0]）
			rangeVal[0]?=?Data.mat[i][axis];
		if?（Data.mat[i][axis]			rangeVal[1]?=?Data.mat[i][axis];
	}
}

vector?stumpClassify（Matrix?Data?int?axis?double?threshVal?string?threshIneq）
{
	vector?retArray（Data.col?1）;
	for?（int?i?=?0;?i?	{
		if?（threshIneq?==?“lt“）
		{
			if?（Data.mat[i][axis]?<=?threshVal）
			{
				retArray[i]?=?-1;
			}
		}
		else
		{
			if?（Data.mat[i][axis]?>?threshVal）
			{
				retArray[i]?=?-1;
			}
		}
	}
	return?retArray;
}

//return?最小的誤差
double?buildStump（Matrix?&dataMatrix?Matrix?&labelMat?Stump?&bestStump?vector?&bestClasEst?vector?&D）
{
	int?m?=?dataMatrix.col;//行
	int?n?=?dataMatrix.row;//列
	double?numSteps?=?10.0;
	vectorrangeVal;
	vectorpredictedVals;
	vectorthreshIneq{?“lt““gt“?};
	double?minError?=?INT_MAX;
	for?（int?i?=?0;?i?	{
		rangeSize（dataMatrix?i?rangeVal）;
		double?rangeMin?=?rangeVal[1];
		double?rangeMax?=?rangeVal[0];
		double?stepSize?=?（rangeMax?-?rangeMin）?/?numSteps;
		for?（int?j?=?-1;?j?		{
			for?（int?k?=?0;?k?			{
				double?threshVal?=?rangeMin?+?j?*?stepSize;
				predictedVals?=?stumpClassify（dataMatrix?i?threshVal?threshIneq[k]）;
				vectorerrArr（m?1）;
				for?（int?ii?=?0;?ii?				{
					if?（predictedVals[ii]?==?labelMat.mat[ii][0]）
					{
						errArr[ii]?=?0;
					}
				}
				double?weightedError?=?0.0;
				for?（int?ii?=?0;?ii?				{
					weightedError?+=?D[ii]?*?errArr[ii];
				}
				//????????????????cout<<“split:?dim?“<				//????????????????cout<<“?the?weighted?error?is?“<				if?（weightedError?				{
					minError?=?weightedError;
					bestClasEst?=?predictedVals;
					bestStump.stumpDim[“dim“]?=?i;
					bestStump.stumpThresh[“thresh“]?=?threshVal;
					bestStump.stumpIneq[“ineq“]?=?threshIneq[k];
				}
			}
		}
	}
	return?minError;
}

//符號函數
int?sign（const?double?x）
{
	if?（x?>?0）
	{
		return?1;
	}
	else?if?（x?	{
		return?-1;
	}
	else
		return?0;
}

double?max（double?a?double?b）?{
	if?（a?>?b）
		return?a;
	else
		return?b;
}

vector?adaBoostTrainDS（Matrix?&dataMatrix?Matrix?&labelMat?int?numIt?=?40）
{
	vectorw

?屬性????????????大小?????日期????時間???名稱
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????.CA....?????13547??2017-05-20?00:13??機器學習\data\adaboost.txt

????.CA....???????144??2017-05-20?00:13??機器學習\data\email\ham\1.txt

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????.CA....???????172??2017-05-20?00:13??機器學習\data\email\ham\12.txt

????.CA....???????164??2017-05-20?00:13??機器學習\data\email\ham\13.txt

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????.CA....???????522??2017-05-20?00:13??機器學習\data\email\ham\15.txt

????.CA....????????90??2017-05-20?00:13??機器學習\data\email\ham\16.txt

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????.CA....????????88??2017-05-20?00:13??機器學習\data\email\ham\25.txt

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????.CA....??????1458??2017-05-20?00:13??機器學習\data\email\ham\6.txt

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????.CA....???????634??2017-05-20?00:13??機器學習\data\email\ham\8.txt

????.CA....???????142??2017-05-20?00:13??機器學習\data\email\ham\9.txt

????.CA....???????235??2017-05-20?00:13??機器學習\data\email\spam\1.txt

????.CA....???????212??2017-05-20?00:13??機器學習\data\email\spam\10.txt

????.CA....???????402??2017-05-20?00:13??機器學習\data\email\spam\11.txt

????.CA....???????182??2017-05-20?00:13??機器學習\data\email\spam\12.txt

............此處省略88個文件信息

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