0
votes
0answers
15 views

Softmax regression or $K$ binary logistic regression

For a multi-class classification problem, we can use $K$ binary logistic classifiers, or one softmax regression classifier, so how to make the choice between the two? IMHO, the $K$ binary logistic ...
0
votes
0answers
7 views

Use a different loss function for cross validation in liblinear

I am trying to learn a L2 regularized Logistic regression model in liblinear. I need a way to specify the C parameter which I do by cross validation. However, the loss/accuracy measure in cross ...
0
votes
0answers
6 views

Specifying the validation dataset for liblinear

I am trying to use the liblinear logistic regression model with L2 regularization. I don't want the training data to be splitted for the cross validation. I want to specify my own validation set for ...
0
votes
1answer
22 views

how to handle (many) false positives in training dataset for logistic regression classifier

I want to train a logistic regression dataset. I have a quite big training data set ( >100 000) and have around 10 features I can train on. Half of my training data is negative training data and I ...
1
vote
1answer
60 views

Example of how the log-sum-exp trick works in Naive Bayes

I have read about the log-sum-exp trick in many places (e.g. here, and here) but have never seen an example of how it is applied specifically to the Naive Bayes classifier (e.g. with discrete features ...
0
votes
1answer
28 views

Data preparation and machine algo for ad click prediction

I am an ml noob. I have a task at hand of predicting click probability given user information like city, state, os version, os family, device, browser family browser version, city, etc. I have been ...
0
votes
1answer
39 views

What is the difference between Binary Clasification and Multiclass classification?

Apology for posting almost one question daily. I am trying to learn some aspects of Statistical Machine learning, so every day many questions coming and if I am not finding answer in my offline peer ...
1
vote
1answer
31 views

Is there a stats tool for this analysis I run in excel?

I am trying to find a statistical or machine learning tool that replicates this analysis I am doing manually in excel. Each row in my data set is a user. ...
0
votes
1answer
111 views

Intuitive explanation of Bayesian logistic regression?

I'm looking for an intuitive explanation of Bayesian Logistic Regression (I'm using it for texts if that's relevant). It seems that this article presents it, but it's, uh, way too mathy. Thanks!
0
votes
1answer
25 views

How can I apply LR with non-linear features?

My training data looks like this: ...
1
vote
0answers
51 views

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique?

How can I improve the accuracy of my logistic regression code, which tests the accuracy using the 10-fold cross-validation technique? I have implemented this code using ...
0
votes
0answers
33 views

Machine learning visualize dataset obtained from machine learning

I have analyzed text by finding sentiments of it. Basically have a huge file with text and its associated sentiment. Obtained by doing Machine learning. Used logistic regression algorithm. Now I want ...
0
votes
0answers
19 views

How can I use logistic regression with categorical variables? [duplicate]

I want to use logistic regression for binary classification on a dataset. I have 14 features in the dataset, and all but one are continuous. I have one categorical variable that represents a ...
0
votes
2answers
68 views

Question regarding parameters and variable selection in Mahout algorithm for logistic regression

Below is the list of parameters in Mahout logistic regression. What does "passes" mean? In detail please --passes passes the number of times to pass over the input data ...
3
votes
0answers
42 views

What is the posterior probability of the data given the model used for model averaging with Bayesian Logistic Regression?

I am trying to learn about Bayesian Model Averaging using Bayesian Logistic Regression (Genkin, A., Lewis, D. D., & Madigan, D. (2007). Large-scale Bayesian logistic regression for text ...
0
votes
2answers
60 views

Ensemble of models with different feature spaces

BACKGROUND I have data in which the dependent variable is binary with a highly-skewed distribution: <1% records are 1 (doers), >99% records are 0 (non-doers). I'm using logistic regression to ...
3
votes
2answers
159 views

How to calculate p values in logistic regression with gradient descent algorithm

In logistic regression, the gradient descent algorithm for calculating coefficients can be described this way: Until convergence, do $$ \beta := \beta + \alpha \frac{\partial L}{\partial \beta} ...
0
votes
1answer
197 views

Beginner - How can I use ranked values in my Logistic Regression?

I am running a Logistic Regression on some data to predict if a webpage is "good" or "bad". I got the dataset from a finished Kaggle competiton here (train.tsv). I extract the second column of this ...
0
votes
1answer
108 views

Bootstrap aggregation (bagging) of logistic regression classifiers

So I'm taking N bootstrap samples and training N logistic regression classifiers on these samples. Each classifier gives me some probability of being in a binary class and then I average these N ...
0
votes
0answers
48 views

How to decide the number of Hidden layers and number of neurons in an Artificial neural network?

How to decide the number of Hidden layers and number of neurons in an Artificial neural network ? I am having an artificial neural network for a rainfall prediction application which is having four ...
1
vote
2answers
130 views

How to improve a Fraud Classification Model?

I built a classification model (Logistic Regression) in order to classify data in Fraud or Not Fraud. This data is related with online CNP (Card Not Present) transactions and after choosing some ...
1
vote
1answer
360 views

Logistic Regression\SVM implementation in Mahout

I am currently working on sentimental analysis of twitter data for one of telecom company data.I am loading the data into HDFS and using Mahout's Naive Bayes Classifier for predicting the sentiments ...
0
votes
1answer
107 views

Machine learning with trinomial features

I have 100,000 students who have each answered some multiple choice questions. Given their performance I want to work out what the chances are of a particular student answering the next question ...
2
votes
3answers
204 views

Machine Learning to Predict Class Probabilities

I am looking for classifiers that output probabilties that examples belong to one of two classes. I know of logistic regression and naive Bayes, but can you tell me of others that work in a similar ...
0
votes
2answers
303 views

Differences Between Logistic Regression in Statistics and in Machine Learning

I just found out that machine learning also has logistic regression as one of its methods. Can someone please tell me the differences between logistic regression in statistics and machine learning? ...
1
vote
2answers
123 views

Correlated features produce strange weights in Logistic Regression

I have a data set with highly positively correlated features that I'm classifying with LR. AFAIK correlated weights are not a problem in the same way they are in Naive Bayes - overcounting will not ...
9
votes
2answers
564 views

Intuition behind logistic regression

Recently I began studying machine learning, however I failed to grasp the intuition behind logistic regression. The following are the facts about logistic regression that I understand. As the ...
1
vote
1answer
146 views

Machine Learning System Design: a practical advice

Recently, I stared working on a machine learning competition hosted on Kagge.com. As the first step, a quick and dirty system was developed using Logistic Regression (LR). After running the system ...
5
votes
1answer
307 views

Why does my ROC curve look like this (is it correct?)

I have a ROC curve generated for a multivariate logistic regression. Does it look correct? This is what I've done: Solve $\theta_0 + \theta_1X_1 + \theta_2X_2 ... = Y$ for the $\theta$s Iterate ...
1
vote
0answers
95 views

Validating logistic regression - formulas needed for simulation

This is related to a data classification problem having a Boolean output variable. Summary: Once I perform the ML task using Logistic regression, I get the required coefficients. I use the ...
4
votes
3answers
544 views

How do you report percentage accuracy for glmnet logistic regression?

I am using glmnet where my dependent variable is binary (class 0, class 1). I want to report percentage accuracy of the model. So I use the ...
1
vote
2answers
159 views

Is there overfitting in my modelling approach despite cross-vaidation?

My model is predicting a binomial dependent variable with a rich feature space of 20,000 independent variables. I am using the penalized logistic regression from the glmnet package, which works for ...
5
votes
3answers
102 views

Sharing a model trained on confidential data

I have a regularized logistic regression model using scikit-learn and would like to share it with others, however the data it is trained on is confidential and must remain protected. The model uses ...
3
votes
0answers
360 views

Online logistic regression? [duplicate]

Here is my problem: I am developing an embedded system for some classification task. I am using Logistic Regression as my classifier. Now I train my classifier, and download my model on to my machine. ...
0
votes
0answers
134 views

Fitting a logistic regression using lassoglm in matlab [duplicate]

I am fitting a logistic regression model using lassoglm in matlab. I issued the following command ...
-1
votes
1answer
68 views

How does Logistic regression classifier modelize the dataset?

I'm working on a system that be able to detect the hand contour. So I have 270 instance in my dataset: 7 class of hand contour, 8 feature vectors of each instance. Firstly, I used Weka to determine ...
2
votes
1answer
472 views

Logistic regression as classifier and overfitting

I am using logistic regression to classify data into two classes. The variable to predict (Y) is either 0 or 1. I have found a rather good estimation of Y by logistic regression, and ended up using ...
3
votes
0answers
111 views

Using priors to detect an effect? logistic Bayesian regression

I have designed an idea and am looking for similar approaches in other literature/areas or if I have applied the Bayesian concepts wrongly. Here is a statement of my problem: I am modeling the ...
1
vote
0answers
197 views

Explain ridge in the log-likelihood for Logistic Regression classifier

What does the ridge parameter change in a Logistic Regression classifier as for example implemented in Weka Logistic classifier "Parameter -R ridge". The paper describing the underlying theory: Ridge ...
3
votes
1answer
542 views

Logistic regression: how to choose negative examples for training set

I want to predict the probability of rain based on the measured weather parameters like temperature, humidity, etc. Let's not get into why I want to do that despite the fact that weather websites ...
4
votes
2answers
764 views

Importance of variables in logistic regression

I am probably dealing with a problem that has probably been solved a hundred times before, but I'm not sure where to find the answer. When using logistic regression, given many features $x_1,...,x_n$ ...
5
votes
2answers
2k views

How to combine results of logistic regression and random forest?

I am new to machine learning. I applied logistic regression and random forest on a same dataset. So I get variable importance (absolute coefficient for logistic regression and variable importance for ...
7
votes
1answer
174 views

Logistic input with Gaussian noise

Both the logistic function and standard deviation are usually denoted $\sigma$. I'll use $\sigma(x) = 1/(1+\exp(-x))$ and $s$ for standard deviation. I have a logistic neuron with a random input ...
3
votes
2answers
563 views

SVM prediction sensitivity when compared to neural networks and logistic regression

Basically I want to classify a rather rare status (about 2% of the 2000) with some predictors. I have used logistic regression, neural network, and Support Vector Machines to do it. All the ...
2
votes
1answer
509 views

Logistic Regression with weighted instances

I'm working on implementing a logistic regression algorithm in code. It's based this link. Unfortunately, the paper doesn't talk about weighting the individual examples $x_{i}$. I think the relevant ...
0
votes
1answer
795 views

Logistic Regression Algorithm?

I am studying on some Machine Learning concepts. I am looking for logistic regression(multiclass) and logistic regression classifier and I should learn how to change it to penalize large weights. I ...
0
votes
1answer
130 views

Algorithm convergence with logistic classifier

I am doing a college classification project, in which I am required to classify some handwritten digits. Assume that my input is a N*D where D is the number of features in each input sample and I need ...
0
votes
2answers
73 views

logistic regression always yielding increasing f'n when should sometimes be decreasing (using R)

I'm modeling a set of outcome data the depends on two parameters: time, T -100 < A < 100 I've done logistic regression using R with the command: ...
4
votes
1answer
178 views

Shifted intercepts in logistic regression

I have a question about the effects of shifting the intercept in a logistic fit on the mean of a particular transformation of the scores. Here is the notation I will be using for the question. The ...
2
votes
0answers
204 views

Standardize/normalize power law distribution for machine learning

If my data follows a normal distribution I can standardize it for a machine learning algorithm, e.g. logistic regression, by subtracting the mean and dividing the result by the standard deviation. ...