Mahalanobis Distance

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Evaluation of clustering for familiarization with k-means

On the evaluation of clustering around k-means for digital transformation, artificial intelligence, and machine learning tasks curse of dimensionality, Mahalanobis distance, Davies-Bouldin index, Dunn index, squared error, RSME, cluster number estimation, inter-cluster density, intra-cluster density
最適化:Optimization

Protected: Anomaly detection by T2 method for hoteling-Mahalanobis distance and chi-square distribution

Anomaly and change detection using the T2 method (Mahalanobis distance) of hoteling used in digital transformation and artificial intelligence tasks.
推論技術:inference Technology

Protected: Classification (3) Probabilistic Discriminant Function(Logistic, Softmax Regression) and Local Learning(K-nearest neighbor method, kernel density estimation)

Probabilistic discriminant functions and local learning used in classifiers for data classification
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