Landslides play an important role in this world. The landslide affects hundreds and thousands of people and is economically vulnerable. The causes of landslides are mainly caused by rain, earthquake and so on. This paper helps to use the method for classification of landslide detection. Subsequently, the construction of the classification algorithm depends on the global-landslide dataset. The main purpose of this method to improve the performance of machine learning ensemble classifiers is to perform better in terms of classification accuracy and execution time based on multiboost, bagging, subspace discrimination and subspace KNN.

landslide, clustering techniques, Machine Learning, k-means, ensemble classifiers

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