Questions tagged [naive-bayes]

A naive Bayes classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong independence assumptions. A more descriptive term for the underlying probability model would be "independent feature model".

Filter by
Sorted by
Tagged with
1
vote
0answers
273 views

How to derive $p(y = k | x)$ for a class-conditional gaussian bayes model?

If we have a Gaussian model with diagonal covariance matrices and shared variances, how do we expand the equation? We have class labels y = (1, 2...,K) and a vector of D features x = (x1, x2, xD). I ...
0
votes
1answer
24 views

Missing Value because observation didn't happened

I need help how to deal with missing value to fit logistic regression or naive Bayes. I need to analyze who will likely to purchase the product and I have datasets looks like this. As you can see, ...
0
votes
1answer
3k views

Naive Bayes with Laplace Smoothing (k = 1)

I used R to predict the event A = "yes" given certain parameters for B1, B2. The results are P(A = "yes"|B1 = "a", B2 = "b") = 0.88. And P(A = "no"|B1 = "a", B2 = "b") = 0.12. But when I did it in ...
2
votes
1answer
5k views

Poor multiclass classification using Caret in R [closed]

I have 5 continuous variables with 211 rows of data and each row is assigned a region, there are 7 possible regions in total. I wish to build a machine learning model that classifies an unseen row of ...
0
votes
0answers
139 views

Generate a probabilistic dictionary with naive bayes

I want to make quantitative content analyses with a naive bayes algorithm. The analyses contain 10000 documents. However, I don´t want to encode 10000 documents manually. So the goal is to train the ...
0
votes
0answers
149 views

Right sequence of events with simple classification (Naive Bayes and Decision Tree)

I'm implementing Naive Bayes and a Decision Tree on the same data, and I need to cross validate with Kfold. Do I have the right sequence of events? Overall, does it make sense or am I ...
1
vote
3answers
1k views

Is there any relationship between Naive Bayes and Hidden Markov model?

Is there any relationship between Naive Bayes and Hidden Markov model? Can we derive one from another?
0
votes
1answer
522 views

Matrix dot product in gaussian multivariate distribution

I am having a bit of trouble understanding how the matrix multiplication is carried out in the exponent term of the multivariate gaussian distribution. I am going to call the covariance matrix C. ...
0
votes
2answers
177 views

Text classification for classes whose probabilities do not add to 1

I have training data that classifies articles (article title and a summary) to one of two classes, let's say class A and class B I want to be able to classify new articles. The problem is, the new ...
0
votes
0answers
55 views

What set of parameters should I choose for Naive bayes and GBM models so that it creates minimal fitting error?

I understand that different set of parameters has to be chosen for each model so as to avoid under or over fitting. But is there is a 'safe set' of parameters which can be used for the widest range of ...
1
vote
1answer
1k views

Text classification beginner steps

I've created a data set containing title, abstract and keywords of scientific articles, I ...
2
votes
1answer
650 views

Using Naïve Bayes to predict disease occurence

I have a dataset concerning patients with information about their diseases and symptoms. I want to estimate probability of $P(disease_i = TRUE|symptom_j = TRUE)$. My intuition is that I should use a ...
1
vote
2answers
123 views

Bayes classifier problem in §3.1.2 of “Temporal Data Mining” by T.Mitsa

In book "Temporal Data Mining" by T.Mitsa, the problem given to illustrate Bayesian classification consists in the following training set of medical records: ...
2
votes
2answers
4k views

How to explain low performance of naive Bayes on a dataset

I'm working on a project from Udacity's ml nd, finding donors, I'm making the initial test using three algorithms: LogisticRegression -> RED GaussianNB -> Green AdaBoostClassifier -> Blue This ...
0
votes
1answer
657 views

How to classify mixed data?

I am trying to do some classification tasks on mixed data set (Hepatitis data set)from UCI ,I will apply SVM and Naive Bayes in R & WEKA, both of them can not handle mixed data directly. Naive ...
1
vote
0answers
30 views

Bayesian Decision Theory - Self Study [duplicate]

Consider a naive Bayes classier with a binary class $Y ∈ {0, 1}$ and three binary features $X_1, X_2, X_3$ ∈ {0, 1}. You are given a set $D$ of $n$ training examples, i.e. D={$(x^{(1)}_1, x^{(1)}_2, ...
3
votes
2answers
427 views

Exercise: Should we trust our naive bayes or a human “guru”?

This is from an exercise about the cost of missclassifications using a Naive Bayes classifier. We know that for some example which has three binary features $x_1,x_2,x_3$ the posterior is $P(Y = 1 | ...
14
votes
1answer
8k views

Why is the naive bayes classifier optimal for 0-1 loss?

The Naive Bayes classifier is the classifier which assigns items $x$ to a class $C$ based on the maximizing the posterior $P(C|x)$ for class-membership, and assumes that the features of the items are ...
2
votes
1answer
177 views

equations for removing noisy, indecisive or too rare features from Naive Bayes

I am looking for formulas/equations/criteria that identify which words from the feature set dictionary are noisy/indecisive or too rare. For example, if the dictionary is let's say 5000 words and the ...
0
votes
1answer
2k views

How can we use Naive Bayes classifier for categorical features? What if some features are numerical?

How can we use Naive Bayes classifier for categorical features? What if some features are numerical?
3
votes
1answer
2k views

Minimizing False Negatives with Multinomial Naive Bayes

I currently have a problem where I am trying to classify medical abstracts where some are relevant and some aren't. I have tried an SVM, Multinomial Naive Bayes and Random Forest, and found the MNB ...
2
votes
1answer
65 views

Calculate Naive Baysian classifier

I'm preparing Dell EMC Associate data science certificate. The following is one of the mock questions and I'm having problem to calculate it by hand and need help. The correct answer is $Y=1$, $...
2
votes
0answers
1k views

How do we interpret the output of the Naive Bayes' classifier in e1071 package?

I am executing the code given at Sentiment analysis with machine learning in R. While executing this code, I am trying to examine the contents of the object 'classifier'. The conditional probability ...
0
votes
1answer
908 views

Training both positive and negative data with naive bayesian classification? [closed]

This might not be the best forum for this question so please forgive me. So I was demo'ed a custom naive bayesian classifier that accepted both positive & negative training data. An example: "I ...
0
votes
0answers
178 views

How to deal with skewed distributions with DNNs?

Suppose I have skewed distributions of classes in train set. How should I deal with it? Just train and network will deal itself? Or some methods are good? For example, can I artificially make ...
1
vote
1answer
79 views

Just How Independent are Events Anyways

I want to describe a thought experiment to explore independent events, and whether they may actually be linked. You are given a set of independent coin generators. Coin generators are true random ...
1
vote
1answer
785 views

Reduction in number of terms to estimate in naive bayes classifier

In the NB classifier, we have instances with $n$ attributes ($x = (a_1,\dots, a_n)$) values in a finite set $V$ and we want to find the most probable classification (max a posteriori classification) \...
4
votes
0answers
1k views

How to use LDA to predict topic proportion for new document?

I'm interested to learn how I can use a trained LDA (Latent Dirichlet Allocation) model to make predictions on the topic proportion of a new, unseen document using Naive Bayes. Let $z \in \{1, 2, ......
2
votes
0answers
432 views

Online learning algorithm not depending on the order of the data?

Are there any online learning algorithm that do not depend on the order of arrival of the data ? I am looking for algorithms that, given a sequence of data $(x_i,y_i)_{i\in[1,n]}$ : Will produce ...
3
votes
0answers
809 views

Naive Bayes vs. logistic regression

I'm working with credit scoring models. Here's what I know: Let Y be the binary outcome variable, $Y \in \{0,1\}$ where $Y = 1$ is the outcome of default and $X = (X_{1},...,X_{m})$ be the random ...
1
vote
1answer
79 views

Text Classification Naive Bayes not working as expected

I am trying to use Naive Bayes to perform text classification. I have two classes A and B. I am mainly interested in identifying class A. Description about the dataset: Some of the text contents ...
3
votes
2answers
790 views

How to Avoid Overfitting in Spam Classification with Text and Numeric Features

In making a document classifier with scikit-learn, I could easily do so with a straightforward Naive Bayes (NB) classifier like MultinomialNB. However, I also have ...
2
votes
1answer
3k views

Why do we need Laplace smoothing in Naive Bayes while logarithm may resolve the problem?

In Naive Bayes algorithm, we use $$P(c)P(x_1|c)P(x_2|c)...p(x_n|c)\space\space (*)$$ to decide about the class of a sample $\textbf{x} =(x_1,...,x_n)$. It is possible that for a class $c$, a feature $...
5
votes
1answer
2k views

In layman's terms, why is Naive Bayes the dominant algorithm used for text-classification?

While I realize choosing the "right" algorithm can vary depending on the task at hand, I'm curious as to why Naive Bayes is quite often used for things like spam-classification or sentiment-analysis. ...
1
vote
3answers
3k views

binary and multiclass classifiers

I have a simple yes/no problem so I was naturally inclined towards using a binary classifier because I was reading the book, A Course in Machine Learning by Hal Daumé III and I quote from it: [ Binary ...
1
vote
1answer
7k views

Laplace smoothing and naive bayes

If I want to use naive bayes with laplace smoothing and therefore add 1 to probabilities with the value of 0, what does this mean for probabilities which have the actual value of 1?
9
votes
1answer
2k views

Is Naive Bayes becoming more popular? Why?

This is the google trends result obtained for "Naive Bayes" phrase from Jan 2004-April 2017 (link). According to this figure, the search ratio for "Naive Bayes" in April 2017 is about %25 higher than ...
3
votes
0answers
2k views

Classification on highly skewed dataset

I have two classes A and B. 98% of the data belongs to class A and 2% of it belongs to class B. Size of the entire dataset is about 2000. I am interested in correctly classifying all the data points ...
0
votes
0answers
190 views

Multinomial Naive Bayes: Should we club (combine) infrequent feature-categories?

Let's say we are using multinomial naive bayes to perform a classification task based on ONE categorical feature. As an example, the categorical feature could be a "Store-ID" and each training ...
2
votes
1answer
2k views

Naive Bayes and independence

In every example I see(spam, negative vs positive tweet , weather study...) there is always the assumption that the input features (or variables) are independent. In order for me to be able to ...
6
votes
2answers
4k views

what is the “learning” that takes place in Naive Bayes?

As I recall algorithms like nearest neighbor don't build a model based on training data and then apply that model to test data. It just takes each new instance and compares it to all the data to find ...
0
votes
1answer
40 views

What sort of analysis method is most appropriate for computer monitoring data that includes samples at a given time?

I'm interested in what sort of modelling is best suited for data that includes samples collected at different times. My use case is to do with computer monitoring, so for the initial case assume that ...
4
votes
2answers
913 views

How to use TFIDF-vectors with Multinomial Naive-Bayes?

Say we have used the TFIDF transform to encode documents into continuous-valued features. How would we now use this as input to a Naive Bayes classifier? Bernoulli naive-bayes is out, because our ...
2
votes
0answers
514 views

Gaussian Naive Bayes sensitive to feature scaling

I'm using a GNB algorithm. As to my knowledge it should be insensitive to feature scaling. However, when I standardize (z-score) or normalize (min-max scaling) those of my features that have a very ...
0
votes
0answers
557 views

Classifiers for small data sets and low dimensional features?

I have a small data set (under 100 samples) and 5 input features. I often hear about how neural networks are prone to overfitting under such conditions and that naive Bayes is likely to underfit. ...
1
vote
2answers
75 views

Text detection, Naive Bayes: How to rate results?

Is there a way to rate the results provided by Naive Bayes algorithm? I mean, if NB detects "I love to play football" and label it as "tennis", is there a way to improve the detection by saying to NB ...
0
votes
1answer
36 views

Need suggestion/guide on how to estimate unknown bayesian priors

Suppose I can only observe people who visit Starbucks. My posterior probabilities will be like $\Pr(\text{male} \mid \text{visits Starbucks})$, $\Pr(\text{has hair} \mid \text{visits Starbucks})$, ...
0
votes
1answer
277 views

How to use Naive Bayes with “not found” label?

I'm trying to do text detection thanks to Naive Bayes Algorithm. If I teach my tool: "Football is a great hobby" and assign it to the label "football", I'm totally fine with it detecting "I play ...
4
votes
2answers
3k views

Confused among Gaussian, Multinomial and Binomial Naive Bayes for Text Classification

I am doing text classification but I am confused which Naive Bayes model I should use. What I understood by reading answers from couple of places that Gaussian Naive Bayes can be used if the attribute ...
1
vote
0answers
51 views

Can inferencing come from incomplete rule sets?

I have some data for medical diagnosis, consisting of some rules about relationship of diseases and their symptoms, for example disease D1 frequently has symptom S1 ...

1
3 4
5
6 7
12