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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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手写体数字识别的训练数据库(MNIST)。
收集了500多位实验者的共60000个样本。-THE MNIST DATABASE of handwritten digits
Four files are available on this site:
train-images-idx3-ubyte.gz: training set images (9912422 bytes)
train-labels-idx1-ubyte.gz: training set label
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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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在这个项目中,我们的目标是建立一个识别和大小231x231图像呈现对象分类系统。我们得到了一组训练图像,每四个标签之一:1飞机;汽车2;3马,否则。我们提供了两个特点:一是方向梯度直方图(HOG),其尺寸为5408;另一个是overfeat ImageNet美国有线电视新闻网的特点,其尺寸37000。关于测试图像,我们只给出了每个图像的功能,没有标签,结果判断由平地机。我们的目标是提供二进制和多个预测。平衡错误率(BER)是我们的性能评估。为了解决这个问题,我们首先减少PCA的问题的维数,处理不
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这是MNIST数据库(一个手写数字的数据库,它提供了六万的训练集和一万的测试集,它的图片是被规范处理过的,28*28的灰度图)
总共4个文件:
train-labels-idx1-ubyte: training set labels
t10k-images-idx3-ubyte:? test set images
t10k-labels-idx1-ubyte:? test set labels
train-images-idx3-ubyte: training set images(T
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