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It includes non-supervised classification methods such as principal component analysis (PCA) and supervised classification methods such as partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA).
These results were much better than the Linear Discriminant Analysis (LDA) and Decision Trees (CART) supervised classification methods.
Numerous supervised classification methods can be used to achieve that.
Supervised classification methods usually take a number of labeled samples to train the classifiers, and the classification accuracy depends on the selected training samples [2].
Supervised classification methods, such as Support Vector Machines [48], Naïve Bayes [49] or ensembles [50, 51] have been deployed to perform sentiment analysis in multiple research projects.
The supervised classification methods include support vector machine (SVM) and Linear Discriminant Analysis (LDA), whilst the used unsupervised include K-means and Bayes.
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The occurrence of such minerals are detected and confirmed by SAM supervised classification method.
According to the process of building earthquake damage information extraction shown in Fig. 3, the Wishart supervised classification method was performed on the PolSAR data after POA compensation.
All images were mosaicked and the minimum distance technique supervised classification method [ 29] was used to classify images into 4 land cover types most-related to flying fox habitat, including forest, irrigated vegetation, settlement/rainfed vegetation, and bodies of water.
In the machine learning method, supervised classification with compound chemical structure similarity was performed for each human protein (see the METHODS section for more details).
For comparison, the results of both the proposed method and the method using Wishart supervised classification directly without POA compensation and CRDbl Vol, which is termed direct Wishart supervised classification (DWSC), are listed in Table 1.
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