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费希尔线性判别分析代码
Find the Fisher linear separator w (a column vector).
X is is the training set (X is a matrix. Each row of X
is a vector containing the features of a single sample). y is
a column vector with the labels of the training set (1
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分类非平衡数据的SMOTEboost算法-This code implements SMOTEBoost. SMOTEBoost is an algorithm to handle class
imbalance problem in data with discrete class labels. It uses a combination of
SMOTE and the standard boosting procedure AdaBoost to better model t
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t10k-labels-idx1-ubyte characters set for training
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Performs KNN classification to a set of data points using a given training data and the associated class labels
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选择１７８个样板的５０％作为训练集，另外的作为测试集，用训练集对ＳＶＭ进行训练得到分类模型，再用得到的分类模型对测试集进行类别标签预测。-Select 178 model 50 as the training set, the other as the test set, the SVM training classification model with the training set, and then the classification model by category label
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