Description: 本次大作业利用K‐近邻（K‐Nearest Neighbor）算法，为给定的训练数据集构造了分类器，
并在测试数据集上进行分类预测，同时计算了Accuracy、Precision、Recall和F‐measure，利用
10‐fold的实验方法进行交叉验证。-The big job to use K-neighbor (K-Nearest Neighbor) algorithm, for a given set of training data classifier is constructed, and the test data sets to classify forecasts, while the calculation of the Accuracy, Precision, Recall and F-measure , using 10-fold cross-validation of experimental methods. Platform: |
Size: 1010688 |
Author:andy |
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Description: estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation.-estimate the test accuracy,training accuray and validation accuracy of a neural network with 10-fold cross validation. Platform: |
Size: 1024 |
Author:sak |
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Description: Abstract. This paper describes a system for isolated Kannada handwritten
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89 -Abstract. This paper describes a system for isolated Kannada handwritten
numerals recognition using image fusion method. Several digital
images corresponding to each handwritten numeral are fused to generate
patterns, which are stored in 8x8 matrices, irrespective of the size of images.
The numerals to be recognized are matched using nearest neighbor
classifier with each pattern and the best match pattern is considered as
the recognized numeral.The experimental results show accuracy of 96.2
for 500 images, representing the portion of trained data, with the system
being trained for 1000 images. The recognition result of 91 was
obtained for 250 test numerals other than the trained images. Further to
test the performance of the proposed scheme 4-fold cross validation has
been carried out yielding an accuracy of 89 Platform: |
Size: 197632 |
Author:avi |
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Description: MATLAB cross-validation tool for classification and regression v0.1
FEATURES:
+ K-fold cross validation.
+ Arbitrary train and prediction functions with parameters can be used.
+ Arbitrary loss function can be used.
+ Wrappers for KNN, SVM, GLM, robust regression and decision trees.
+ Wrappers for RMSE, MAD and misclassification loss functions. Platform: |
Size: 3072 |
Author:milk |
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Description: Naive Bayes training and testing with 10-fold cross validation. Train and test data files provided. Platform: |
Size: 13163520 |
Author:sehmetia |
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Description: Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.-Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves. Platform: |
Size: 6144 |
Author:Gang Fu |
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Description: matlab交叉验证cross Validation，把样本集分为训练集和测试集，防止网络出现过拟合，提高网络的泛化能力和预测精度-cross Validation for matlab，to estimate the test accuracy,training accuray and validation accuracy of a neural network Platform: |
Size: 1024 |
Author:周杰伦 |
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Description: 神经网络训练，应用matlab7NN包，用一个隐藏层使用5折交叉验证。-Training the Neural Network
This script is something that I did for a course at Uni. It uses the Neural Networking package provided with MatLab 7 unfortunately I m not sure if it s available with the earlier versions of MatLab. This script uses the command lines for the package to perform the task, otherwise you can use the GUI that s provided, by typing nntool. This script shows 5 fold cross validation on a neural network with 1 hidden layer with a variable number of hidden nodes along with a single output. The entire process is done 2 times, because each time the data was encoded in a different manner, which in turn altered how much the Neural Network was able to learn from the data. Below you ll find the script to collect the data for the final results. Platform: |
Size: 2048 |
Author:kingking |
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Description: 该程序用于十折交叉验证，对原数据集进行随机划分。-The procedure used for the ten-fold cross-validation randomly divided the original data set. Platform: |
Size: 1024 |
Author:魏秀参 |
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Description: 十折交叉验证程序，用贝叶斯公式进行具体计算验证在已有条件下是否去打球。-Calculate average decision accurate for Table 1 using Ten-fold-cross validation. Platform: |
Size: 4096 |
Author:郑先木 |
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Description: 十折交叉验证算法的代码，我用的比较简单，希望大家能够喜欢-Ten-fold cross-validation algorithm code, I use relatively simple, hope that we can love Platform: |
Size: 12288 |
Author:李阗智 |
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Search - fold cross validation