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特征...
from sklearn.svm import SVC, LinearSVC from sklearn.naive_bayes import GaussianNB from sklearn.ensemble import RandomForestClassifier, GradientBoostingClassifier from sklearn.linear_model import LogisticRegression from sklearn.neighbors import KNeighborsClassifier from sklearn.neural_network import MLPClassifi...
使用伯努利或多项式模型进行条件概率的 Naive Bayes 包装器。 使用Bernoulli 或多项式模型初始化 Naive Bayes 包装类。 构造函数 Python 复制 NBWrapper(model, **kwargs) 参数 展开表 名称说明 model 必需 str 实际模型名称。 方法 展开表 fit 适合Naive Bayes 模型的函数。 get_model 返回Naive...
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, th...
在SQL Server 2008中提供了决策树算法、聚类分析算法、Naive Bayes算法、关联规则算法、时序算法、神经网络算法、线性回归算法等9种常用的数据挖掘算法。 但是,预测建模的实现是基于SQL Server 平台的,平台移植性相对较差。( 4 ) Python Python ( Matrix Laboratory, 矩阵实验室)是美国Mathworks公司开发的应用软件,具备...
from sklearn.naive_bayes import GaussianNB gauss = GaussianNB() gauss.fit(X_train, Y_train) #Using DecisionTreeClassifier from sklearn.tree import DecisionTreeClassifier tree = DecisionTreeClassifier(criterion = 'entropy', random_state = 0) ...
She draws on both rule-based and statistical Naive Bayes methods but does not use neural networks or any dictionaries of words. She does not need a connection to any external API or service either. Once the library has been downloaded, it can be used completely offline. 3. A short history...
This program illustrates some of the main features of Python. First, whitespace is used to nest lines of code; thus the line starting with if falls inside the scope of the previous line starting with for; this ensures that the ing test is performed for each word. Second, Python is object...
azureml.training.tabular.models.calibrated_model azureml.training.tabular.models.differencing_y_transformer azureml.training.tabular.models.forecasting_models azureml.training.tabular.models.forecasting_pipeline_wrapper azureml.training.tabular.models.forecasting_pipeline_w...