naivebayes

来源： https://stackoverflow.com/questions/51968769/getting-feature-importance-in-naive-bayes

问题 I have code like this x_train=data['TOKEN'].loc[:2] y=data['label'].loc[:2] x_test=data['TOKEN'].loc[3:] that contain 3 Data training 1 class each class(-1),(0),(1) and 1 data test #TFIDF training tfidf= TfidfVectorizer(smooth_idf=False,norm=None) x_tfidf2 = tfidf.fit_transform(x_train) tfidfframe_train = pd.DataFrame(x_tfidf_train,columns=tfidf.get_feature_names()) #the output of tfidfframe_train a b c d e f 0 0.0 0.0 0.0 1.477 1.477 1.0 -> class -1 data train doc1 1 0.0 0.0 1.176 0.0 0.0 1

问题 I have code like this x_train=data['TOKEN'].loc[:2] y=data['label'].loc[:2] x_test=data['TOKEN'].loc[3:] that contain 3 Data training 1 class each class(-1),(0),(1) and 1 data test #TFIDF training tfidf= TfidfVectorizer(smooth_idf=False,norm=None) x_tfidf2 = tfidf.fit_transform(x_train) tfidfframe_train = pd.DataFrame(x_tfidf_train,columns=tfidf.get_feature_names()) #the output of tfidfframe_train a b c d e f 0 0.0 0.0 0.0 1.477 1.477 1.0 -> class -1 data train doc1 1 0.0 0.0 1.176 0.0 0.0 1

问题 This code below is suppose to run a bayes classifer for a full covaraince gaussian (http://courses.ee.sun.ac.za/Pattern_Recognition_813/lectures/lecture03/node2.html), but I get two errors when I run the code. They are: RuntimeWarning: Mean of empty slice. warnings.warn("Mean of empty slice.", RuntimeWarning) and RuntimeWarning: Degrees of freedom <= 0 for slice warnings.warn("Degrees of freedom <= 0 for slice", RuntimeWarning) This is my code: def modelFull(train, test): err_train = 0 err

问题 This code below is suppose to run a bayes classifer for a full covaraince gaussian (http://courses.ee.sun.ac.za/Pattern_Recognition_813/lectures/lecture03/node2.html), but I get two errors when I run the code. They are: RuntimeWarning: Mean of empty slice. warnings.warn("Mean of empty slice.", RuntimeWarning) and RuntimeWarning: Degrees of freedom <= 0 for slice warnings.warn("Degrees of freedom <= 0 for slice", RuntimeWarning) This is my code: def modelFull(train, test): err_train = 0 err

问题 Using the iris dataset in R, I'm trying to fit a a Naïve Bayes classifier to the iris training data so I could Produce a confusion matrix of the training data set (predicted vs actual) for the naïve bayes classifier, what is the misclassification rate of the Naïve Bayes Classifier? Here's my code so far: iris$spl=sample.split(iris,SplitRatio=0.8) train=subset(iris, iris$spl==TRUE) test=subset(iris, iris$spl==FALSE) iris.nb <- naiveBayes(Species~.,data = train) iris.nb nb_test_predict <-

问题 Using the iris dataset in R, I'm trying to fit a a Naïve Bayes classifier to the iris training data so I could Produce a confusion matrix of the training data set (predicted vs actual) for the naïve bayes classifier, what is the misclassification rate of the Naïve Bayes Classifier? Here's my code so far: iris$spl=sample.split(iris,SplitRatio=0.8) train=subset(iris, iris$spl==TRUE) test=subset(iris, iris$spl==FALSE) iris.nb <- naiveBayes(Species~.,data = train) iris.nb nb_test_predict <-

问题 I’m working on building predictive classifiers in R on a cancer dataset. I’m using random forest, support vector machine and naive Bayes classifiers. I’m unable to calculate variable importance on SVM and NB models I end up receiving the following error. Error in UseMethod("varImp") : no applicable method for 'varImp' applied to an object of class "c('svm.formula', 'svm')" I would greatly appreciate it if anyone could help me. 回答1: Given library(e1071) model <- svm(Species ~ ., data = iris)

问题 I am new to PyCharm and I have found two codes online on Classification Techniques, using Naive Bayes classification. this code doesn't have an error. but I can see the result, even though I use print() . I'm using library iris dataset. and this is my code import csv import math import random import pandas as pd from sklearn import datasets def loadCsv(filename): #lines = csv.reader(open(r'E:\KULIAH\TUGAS AKHIR\MachineLearning\kananniih.csv')) lines = datasets.load_iris() print(lines) dataset

问题 I am using accord.net. I have successfully implemented the two Decision tree algorithms ID3 and C4.5, now I am trying to implement the Naive Bays algorithm. While there is a lot of sample code on the site, most of it seems to be out of date, or have various issues. The best sample code I have found on the site so far has been here: http://accord-framework.net/docs/html/T_Accord_MachineLearning_Bayes_NaiveBayes_1.htm However, when I try and run that code against my data I get: There are no