Machine learning Path: Python K-mean clustering Kmeans handwritten numerals

Python3 Learning using the API

Using the data set on the Internet, I downloaded him to a local

can download datasets in my git: https://github.com/linyi0604/MachineLearning

Code:

1 ImportNumPy as NP2 ImportPandas as PD3  fromSklearn.clusterImportKmeans4  fromSklearnImportMetrics5 6 " "7 K-Mean-value algorithm:8 1 randomly selected K samples as the center of the K category9 2 from the K sample, select the nearest sample to be the same category as yourself, until all samples are classified.Ten 3 pairs of K-classifications for the Re-computing center sample One 4 repeat from K New Center sample, A If the result of the class is the same as the last one, stop - otherwise repeat 234 -          the " " - " " - The data set originates from the online https://archive.ics.uci.edu/ml/machine-learning-databases/optdigits/ - I downloaded him locally. + Training Sample 3,823, test sample 1797 - the image is represented by a total of 64 dimensions through the 8*8 pixel matrix, and 1 target dimensions represent the number category + " " A  at #1 Preparing Data -Digits_train = Pd.read_csv ("./data/optdigits/optdigits.tra", header=None) -Digits_test = Pd.read_csv ("./data/optdigits/optdigits.tes", header=None) - #extracting 64-dimensional pixel features and 1-dimensional targets from a sample -X_train = Digits_train[np.arange (64)] -Y_train = digits_train[64] inX_test = Digits_test[np.arange (64)] -Y_test = digits_test[64] to  + #2 Building a model - #Initialize Kmeans cluster model Cluster Center number is 10 theKmeans = Kmeans (n_clusters=10) * #Clustering $ Kmeans.fit (X_train)Panax Notoginseng #each test image belongs to the cluster center you -Y_predict =kmeans.predict (x_test) the  +  A #3 Model Evaluation the #performance evaluation with ARI use ARI for model evaluation when clustering has a category + Print("K-Mean-value-clustering Ari value:", Metrics.adjusted_rand_score (Y_test, y_predict)) - " " $ K-Mean-value-clustering Ari value: 0.6673881543921809 $ " " - #if no cluster category is available, evaluate with contour factor

Machine learning Path: Python K-mean clustering Kmeans handwritten numerals