朴素贝叶斯模型(Naive Bayes Model, NBM)是一种基于贝叶斯定理和特征条件独立性假设的分类算法。其核心思想是通过给定特征X的条件下,预测样本属于某类别c的后验概率P(c|X),选择后验概率最大的类别作为分类结果。 基本原理 朴素贝叶斯模型的基本原理基于贝叶斯定理,公式如下: [ P(c|X) = \frac{P(X...
算法封装成类NaiveBayes。 执行model = NaiveBayes(isSmoothing=True) 即实例化朴素贝叶斯分类模型。 isSmoothing为可选参数,默认为True,使用拉普拉斯平滑;若为False,则不使用平滑。 调用model.fit(X__, y_, indexContinuousFeatures_=()) 方法进行训练; X__为存储训练样本特征向量的矩阵,可以有离散值特征和连续值...
from sklearn.model_selectionimporttrain_test_split from sklearn.naive_bayesimportMultinomialNB # Define the vocabulary vocabulary=['good','bad','excellent','poor','great','terrible','awesome','awful','fantastic','horrible']# here the learned vocabulary issetfrom the begining # it is usually c...
import os import sysecs 编码转换模块 import codecs from sklearn.naive_bayes import MultinomialNB from sklearn.feature_extraction.text import CountVectorizer if __name__ == '__main__': # 读取文本构建语料库 corpus = [] labels = [] corpus_test = [] labels_test = [] f = codecs.open("...
Python Code #Import Library of Gaussian Naive Bayes modelfromsklearn.naive_bayesimportGaussianNB import numpy as np #assigning predictor and target variables x=np.array([[-3,7],[ 1,5], [1,2], [-2,0], [2,3], [-4,0], [-1,1], [1,1], [-2,2], [ ...
#导入包 import pandas as pd from sklearn.naive_bayes import GaussianNB#导入高斯分布朴素贝叶斯包 from sklearn.model_selection import train_test_split#导入训练集和测试集划分的包 from sklearn.metrics import accuracy_score#导入计算准确率的包 1. 2. 3. 4. 5. #导入数据集 from sklearn import data...
MultinomialNB(), xtrain_count, train_y, xvalid_count) print "NB, Count Vectors: ", accuracy #特征为词语级别TF-IDF向量的朴素贝叶斯 accuracy = train_model(naive_bayes.MultinomialNB(), xtrain_tfidf, train_y, xvalid_tfidf) print "NB, WordLevel TF-IDF: ", accuracy #特征为多个词语级别TF...
statsimportpearsonrfromsklearn.model_selectionimportGridSearchCVfromsklearn.neighborsimportKNeighborsClassifierfromsklearn.naive_bayesimportMultinomialNBfromsklearn.treeimportDecisionTreeClassifier, export_graphvizfromsklearn.ensembleimportRandomForestClassifierfromsklearn.linear_modelimportLinearRegression, SGDRegressor, ...
下面是使用常用sklearn包的双类 Naive Bayes 分类器的示例代码: Python复制 # The script MUST define a class named Azure Machine LearningModel.# This class MUST at least define the following three methods:# __init__: in which self.model must be assigned,# train: which trains self.model, the...
Naive Bayes*XgboostTCNForecaster 随机梯度下降 (SGD)*随机梯度下降 (SGD)渐进提升 ExponentialSmoothing SeasonalNaive 平均值 Naive SeasonalAverage 使用其他算法: 图像分类多类算法 图像分类多标签算法 图像物体检测算法 NLP 文本分类多标签算法 NLP 文本命名实体识别 (NER) 算法 ...