Gaussian Naive Bayes in Scikit-learn In [26]: from sklearn.naive_bayes import GaussianNB from sklearn.datasets import load_iris from sklearn.cross_validation import train_test_split from sklearn.metrics import accuracy_score In [27]: # Create features' DataFrame and response Series iris = ...
Finally, we have implemented a complete Gaussian naive Bayes classifier in a way that works well with scikit-learn. That means you can use it in pipelines or grid search, for example. In the end, we did a small sanity check by importing scikit-learns own Gaussian naive Bayes classifier ...
Python中的scikit-learn库提供了实现线性判别分析(LDA)和二次判别分析(QDA)的工具。在本博客中,我们将通过几个代码示例探讨如何使用Python进行判别分析。线性判别分析(LDA)线性判别分析(LDA)是一种分类技术,它旨在寻找数据特征的线性组合,从而最大化不同类别 判别分析 数据集 线性判别分析 MATLAB轧钢问题的求解 轧钢...