Questions tagged [naive-bayes-classifier]
Naive Bayes classifiers makes the naive assumption that the features are independent. They make use of Bayes theorem.
204 questions
0
votes
1
answer
514
views
1
vote
0
answers
51
views
Binary classifier on imbalanced dataset yields weird PR curve
I have a dataset with ~6M points, 9 features and two classes. The minority class represents just under 2% of the data. The data is first divided into 100 batches and a different classifier is trained ...
- 111
1
vote
1
answer
82
views
In Naive Bayes classifier how is P(sneezing,builder|flu) = P(sneezing|flu)P(builder|flu)?
Please refer to this literature:
According to Naive Bayes classification algorithm:
$P(sneezing,builder|flu) = P(sneezing|flu)P(builder|flu) $
where sneezing and builder are independent events.
...
- 113
2
votes
1
answer
479
views
Naive Bayes and Support Vector Machine (NBSVM) Classification
I am relatively new to datascience and have a question about NBSVM. I have a two class problem and text data (headlines from the newspaper). I want to use NBSVM to predict whether a headline has the ...
4
votes
1
answer
1k
views
Training textblob with 16k rows of labeled data won't work (only few are working)
I've got labeled data in a csv which looks like:
title,type
Women Jacket A,Clothes
Mens Running Shoes B,Shoes
Children backpack,Bags
and a script:
...
- 183
1
vote
1
answer
651
views
naive bayes classifier for non-binary feature values
Given a training set $\{{(x^{(i)},y^{(i)});i=\{1,...,m}\}\}$ where $x^{(i)}\in\{1,2,...s\}^n$ and $y^{(i)}\in{0,1}$. We model the label as a biased coin with $\theta_0=P(y^{(i)}=0)$ and $1-\theta_0=P(...
- 163
1
vote
1
answer
78
views
Train Naive Based Classifier
For (a) I have calculated $P(G)=\frac{5}{8}$, $P(O|G)=\frac{2}{5}$, $P(B|G)=\frac{1}{5}$, $P(C|G)=\frac{4}{5}$, and $P(A|G)=\frac{4}{5}$. Now how do I calculate the maximum likelihood estimate of ...
- 163
1
vote
1
answer
144
views
Reversing Naive Bayes to find extreme points of data sets
I'd like to know if this is a sensible idea and if there exist any already formed methods to do this (I'm new to the data science area).
Essentially, I have used Naive Bayes to accurately classify ...
- 13
1
vote
3
answers
923
views
Why did Logistic regression perform better than svm? [closed]
I have a data set of movies and their subtitles.My task is to classify them based on their ratings-[R,NR,PG,PG-13,G].
I have tried different ML algorithms and found that Logistic regression out ...
- 117
2
votes
1
answer
26
views
Looking for other opinions on approach to classification problem
I'm looking to implement an "opt-out" filter for my company. The input is short, text-message style messages. A few examples of opt-out messages are:
"remove me from your list"
"remove from list"
"...
- 213
1
vote
1
answer
323
views
Very low probability in naive Bayes classifier 1
I have some training data (TRAIN) and some test data (TEST). Each row of each table contains an observed class (X) and some columns of binary (Y). I'm using a Python script that is intended to predict ...
- 121
1
vote
1
answer
1k
views
Naive Bayes Classifier - Discriminant Function
To classify my samples, I decided to use Naive Bayes classifier, but I coded it, not used built-in library functions.
If I use this equality, I obtain nice classification accuracy: ...
- 113
3
votes
2
answers
1k
views
Avoiding the zero problem
I have a dataset and I'm trying to predict the label for my sample but I couldn't map it since that case never showed here is my sample (I'm using naïve Bayesian method)
X=(Age=middle, has_job=false, ...
- 31
12
votes
1
answer
7k
views
How does Naive Bayes classifier work for continuous variables?
I know that for categorical features we just calculate the prior and likelihood probability assuming conditional independence between the features.
How does it work for continuous variables? How can ...
- 951
2
votes
3
answers
2k
views
Classifier for large number of labels
I have a merchants dataset with 800,000 samples and 18,000 labels. Each sample is associated with a single label and the labels are independent.
An example sample looks like
...
1
vote
2
answers
97
views
Naive Bayes Classifier
Could someone please explain to me how and why can we go from equation $4.3$ to equation $4.4$:
$$\hat{c}= \arg\max_{c \in \mathcal{C}}P(c|d) = \arg\max_{c \in \mathcal{C}}\frac{P(d|c)P(c)}{P(d)}\tag{...
- 746
6
votes
2
answers
4k
views
Effect of outliers on Naive Bayes
Are Naive Bayes algorithms affected by outliers in the data? Suppose there is a data set, does one need to remove outliers before applying Naive Bayes?
- 61
3
votes
2
answers
817
views
How does the naive Bayes classifier handle missing data in testing?
Assume that a classier has been trained already (no missing training data), but a prediction has been requested based on an observation that does not include every feature. How can we handle this ...
1
vote
0
answers
53
views
Dealing with missing n-grams in Naive Bayes classifier
I am doing sentiment analysis on code-mixed text data, i.e English used interchangeably with another language. The dataset I currently have is very small in size, approx 3.5k samples.
I am sure that ...
- 21
1
vote
0
answers
227
views
My naive (ha!) Gaussian Naive Bayes classifier is too slow
I am trying to build a film review classifier where I determine if a given review is positive or negative (w/ Python). I'm trying to avoid any other ML libraries so that I can better understand the ...
- 111
5
votes
4
answers
282
views
Is the prediction algorithm absolutely the same for all linear classifiers?
Is the prediction algorithm absolutely the same for all linear classifiers and linear regression algorithms?
As known, any linear classifier can be described as: ...
- 649
1
vote
0
answers
319
views
One class naive bayes
I have to build one class naive Bayes method for outlier detection based on the likelihood probabilities. I tried to create it using sklearn GaussianNB but it is for multiclass classification. Is ...
- 420
1
vote
1
answer
5k
views
How to calculate Accuracy, Precision, Recall and F1 score based on predict_proba matrix?
I found this link that defines Accuracy, Precision, Recall and ...
- 277
1
vote
1
answer
756
views
Naive bayes, all of the elements in predict_proba output matrix are less than 0.5
I've created a MultinomialNB classifier model by which I'm trying to label some test texts:
...
- 277
1
vote
1
answer
767
views
How to measure uncertainty and prediction errors for a naive Bayesian Classifier?
I have a small dataset of 30 rows and 5 columns (4 features and 1 class). The classifier is used to give the likelihood of occurrence of an incident. thus, the class variable gives the probability of ...
- 133
1
vote
1
answer
949
views
test accuracy of text classification is too less
I have a data set of movies and their subtitles. My task is to classify them based on their ratings - [R, NR, PG, PG-13, G].
I have 13 examples for each class.
I preprocessed the subtitles in the ...
- 117
2
votes
0
answers
410
views
Sentiment Analysis Naive Bayes vs Logistic Regression [closed]
I am doing some sentiment analysis on Twitter data, and I wanted to compare a Naive Bayes Classifier and a Logistic Regression classifier as to if their performance is affected by spell checking the ...
- 21
2
votes
1
answer
1k
views
Collinearity and Outlier Removal
I am playing with a credit fraud detection dataset at Kaggle. An imbalanced dataset with about 0.1% of fraud transaction. The features are 28 PCs out from a PCA exercise done by the data publisher + ...
- 21
1
vote
1
answer
1k
views
How can one use a validation set to reduce overfitting Naive Bayes?
What is the correct procedure for using a validation set to reduce overfitting?
Say I split the data 80:10:10 (training: validation:test). I train on the training set then get 90% accuracy. I apply ...
6
votes
2
answers
3k
views
How to deal with missing data for Bernoulli Naive Bayes?
I am dealing with a dataset of categorical data that looks like this:
...
- 161
1
vote
0
answers
311
views
Laplacian smoothing on Class Probability (Naive bayes)
I am implementing a Naive Bayes classifier in Python from scratch. The instructions I have asks that I incorporate Laplacian Smoothing with K=1 to computing the probability that a message belongs to a ...
2
votes
1
answer
803
views
Predict the corresponding value in one column using a list of values found in another column
Please have a look at this link. This was a question I asked few months back and after some suggestions and exploring I was able to successfully use TFIDF along with MultinomialNB classifier to pretty ...
- 171
2
votes
0
answers
32
views
Conditional Probabilities on store data
I have data on store level purchases, Panel-level purchases and demographic information of loyalty cards.
In the store purchases information, the data consists of a product code which can be assigned ...
- 243
7
votes
3
answers
5k
views
Why does the naive bayes algorithm make the naive assumption that features are independent to each other?
Naive Bayes is called naive because it makes the naive assumption that features have zero correlation with each other. They are independent of each other. Why does ...
- 1,445
1
vote
1
answer
729
views
Is there an API to extract questions and labels from yahoo answers?
I want to work on a ML project which involves the family and relationship category from yahoo answers. I want to extract questions from yahoo answers (only the title) with the label as the category it ...
- 669
0
votes
1
answer
57
views
Bayes Classifier as a general model
Is it correct to argue that the Bayer Classifier is an ideal classifier, which is taken as a model by every other implemented classifier?
- 241
5
votes
1
answer
570
views
How are ANN's, RNN's related to logistic regression and CRF's?
This question is about placing the classes of neural networks in perspective to other models.
In "An Introduction to Conditional Random Fields" by Sutton and McCallum, the following figure is ...
- 209
4
votes
2
answers
1k
views
Naive Bayes for SA in Scikit Learn - how does it work
Okay so i scrape data from the web on movie reviews. I also have already got my own 'dictionary' or 'lexicon' with words and their labels (1-poor, 2-ok, 3-good, 4-very good, 5-excellent).
SO the ...
- 143
2
votes
1
answer
200
views
Doubt in interpretation of Bernoulli Naive Baeyes Algorithm
We say Bernoulli naive bayes assumes gaussian distribution of all continuous features. What happens if I have categorical features also in the dataset?
What type of prior transformation in data is ...
- 435
6
votes
4
answers
1k
views
Naive Bayes Multinomial, independence assumption misunderstood
This is embarrassing but I think I miss understand something.
In multinomial distribution, "while the trials are independent, their outcomes X are dependent because they must be summed to n." wiki
...
- 329
3
votes
2
answers
221
views
Algorithms and tools for ranking text as a job description
We're working on a ranking texts by degree of the similarity to vacancies. We have 4-year data set (≈1M texts) of custom search feeds from social network. We also have vacancies (≈30K) manually ...
- 33
1
vote
1
answer
75
views
Optimize F-Score only for certain classes, disregard other classes
I have a labeled dataset of product reviews where the label is a rating between 1 and 5 and the review is just text.
I use a simple naive Bayes classifier (sklearn) to try to predict a rating given a ...
- 111
1
vote
0
answers
55
views
Processed data cannot build Naive Bayes Classifier model
Having preprocessed data using weka supervised cfssubseteval forward and backward selection, the decision tree model builds and makes prediction well, but naive Bayes do not recognize the same Arff ...
- 21
2
votes
1
answer
4k
views
How to improve Naive Bayes?
I am solving a problem that address this question "What are the Actions that lead to high or low score?"
I have the following Data that consist of text and score , I want to derive the words or ...
- 481
2
votes
1
answer
555
views
Why is spam detection a classification problem and not a class modelling problem
Trying to get my feet wet with machine learning on text.
The most common dataset I've seen in this space is the sms dataset with classes ham and spam.
And the most common and successful approach ...
- 123
5
votes
1
answer
243
views
When to use Multinomial Naive Bayes?
I am working on a text classification problem, and plan on using Naive Bayes based model.
In which cases should I consider using Multinomial Naive Bayes?
- 253
1
vote
1
answer
40
views
Why do classes with fewer words have higher probability?
Given that I have a word that does not occur in any of my documents: newword, and given that I have two classes: class1 and <...
- 111
3
votes
1
answer
10k
views
How does ,the Mutlinomial Bayes's alpha parameter, affects the text classification task?
I would like to know how the alpha parameter, in Multinomial Bayes, affects the text classification task.
I know that this parameter is correlated to the algorithm'...
- 715
1
vote
0
answers
35
views
Find words related to high or low score
I am working on text analysis problem.
Person X can log in his goals and his actions to achieve his goal. Also their score is calculated based on some formula to measure progress of the goal.
For ...
- 481
0
votes
1
answer
67
views
Should I remove features that occur very rarely to build a model?
I am trying ML techniques in language processing.
I have got 3000 short texts and I extract features(words and phrases) from all of them and build a vocabulary. I end up with 6000 od features and most ...
- 123