Multi-label text classification calculation method based on ensemble learning
A technology of text classification and calculation method, which is applied in text database clustering/classification, unstructured text data retrieval, special data processing applications, etc. It can solve the problems of high time complexity, reduce risks, improve training speed, and improve The effect of generalization ability
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[0021] The present invention proposes a multi-label text classification calculation method based on integrated learning, such as figure 1 shown, including:
[0022] Step 1: Preprocess the original data set, segment sentences into individual words, and delete non-keywords;
[0023] Step 2: Use the method of word frequency-inverse text frequency to perform feature extraction and vectorization processing on the text;
[0024] Step 3: Decompose the multi-label learning problem into multiple independent binary classification problems using the binary association method, each binary classification problem corresponds to a label in the label space;
[0025] Step 4: Classify the labels using an ensemble learning algorithm.
[0026] The preprocessing stage is an important task in data set design, and it is crucial to use machine learning methods to preprocess data. Actually, it consists of two subtasks; (1) word segmentation and (2) stopword removal.
[0027] The purpose of word se...
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