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Analysis of efficiency of classification and prediction algorithms (Na¿¿ve Bayes) for Breast Cancer dataset

机译:乳腺癌数据集的分类和预测算法(朴素贝叶斯)的效率分析

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In developed countries death of women due to breast cancer has become regular. Data mining techniques are used to provide the analysis for the classification and prediction algorithms. The algorithms used here are Na¿¿ve Bayes classification algorithm and Na¿¿ve Bayes prediction algorithm. The algorithms are used to classify and predict whether the tumour is either benign or malignant. The data used in the algorithms is taken from the Wisconsin University database. Data sets are used to find the success rate and the error rate.
机译:在发达国家,由于乳腺癌导致的妇女死亡已成为常规。数据挖掘技术用于为分类和预测算法提供分析。此处使用的算法是朴素贝叶斯分类算法和朴素贝叶斯预测算法。该算法用于分类和预测肿瘤是良性还是恶性。算法中使用的数据取自威斯康星大学数据库。数据集用于查找成功率和错误率。

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