# Tagged Questions

62 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 ...
65 views

### Logistic regression and maximum entropy

I have read (e.g. here) that a (multinomial) logistic regressor corresponds to a maximum entropy classifier. My question is, how does one end up with the formula for logistic regression starting with ...
23 views

### Accuracy outcomes puzzle when using logit for prediction

I'm building a predictive logit model for a rare event using 5-fold cross-validation. I have three years of data. I build a model with a training set of years 1 and 2, then I test on the test set with ...
79 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 ...
364 views

### Logistic regression: maximizing true positives - false positives

I have a logistic regression model (fit via glmnet in R with elastic net regularization), and I would like to maximize the difference between true positives and false positives. In order to do this, ...
30 views

### Modeling strategy to produce predicted probabilities for different aggregations

I have a large amount of data (millions of observations) and am trying to produce a predicted probability of a discrete action based on a number of covariates. So far, this is a classic classification ...
150 views

### How to select cut-point for making classifications table for logistic regression?

How can I select cut-points to convert predicted probabilities to predicted responses in order to make a classification table for logistic regression? Should I take different cut-points like .5, .6, ...
125 views

### How can I tell if my binary classifier is any good?

Say I have a data set with 10,000 rows and the target is a binary variable with 1500 positives (1's) and 8500 negatives (0's). I run a model and get predictions on the 0-1 interval. My question is ...
55 views

### Features to represent peaks in time series

I have a dataset of time series that present popularity of words (or phrases). Each words is a list of frequencies according to a timestamp. My purpose is to detect a specific type of spike that leads ...
85 views

### Effective validity of AUROC as performance measure: what about “very high” AUROC values?

The Area Under ROC curve (AUROC) is a quantity used to quantify performance of classifiers. I am currently interested in the most basic drawbacks of using AUROC as unique performance measure. I got ...
60 views

### When to use ridge estimator / naive Bayes

I used the Logistic function in weka, to predict a binary class. I have used SimpleLogistic before, but Logistic also seem to give me good results. I did want to clarify if I understand some things ...
84 views

### Role of coefficients in model selection for logistic regression

I have a model that I am using to predict mortality and it gives me an AUC of 0.799. The R code that I am using would look something like this: ...
344 views

### Online logistic regression?

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. ...
79 views

### What method should I use to identify which variables differentiate between objects of two different classes?

To illustrate the problem posed by the question: Consider the problem of differentiating between consumers who belong to two different segments. I could use a naive or a sophisticated approach as ...
78 views

### How do you generate synthetic sparse binary linguistic data for logistic regression?

I am trying to generate synthetic linguistic data (boolean features) to fit a binary logistic regression model. This is similar to 8260771 on StackOverflow and several synthetic data questions on this ...
345 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 ...
55 views

### Reformulate binary classification: Relative penalty of false positives versus false negatives

I have a training data for a set of insurance claims that I used to train multiple models within R (1. Binomial Logistic regression 2. Naive Bayes 3. k nearest neighbor algorithm) The binomial ...
370 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 $x_1,...,x_n$ ...
414 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 ...
211 views

### Does learning rate have additional meaning in logistic regression?

I try to implement logistic regression with auto-correcting learning rate and I am puzzled by the outcome. At some point the cost of the function gets bigger than previously (to focus on some numbers ...
109 views

### Accuracy vs. simplicity as criteria to select explanatory variables

I want to create a binary model which predicts whether someone has improved his state. I am testing possible variables as explanatory variables in order to make some recommendations. Now my binary ...
804 views

### Interpreting logistic regression

I need to perform a logistic regression to to see if a group of variables which are found to be significantly associated with an outcome (by univariate tests) have significant impact on the outcome ...
262 views

### Multilabel logistic regression

Is there a way to use logistic regression to classify multi-labeled data? By multi-labeled, I mean data that can belong to multiple categories simultaneously. I would like to use this approach to ...
875 views

### How to combine WEKA classifiers

I need to utilize two different classifier to get best classification results. Since, it seems that they complement each other (not sure I am not expert btw). ROC characteristics are given below ...
1k views

### Logistic regression performance with high number of predictors

I'm trying to understand the behavior of logistic regression in high dimensional problems (i.e. when you are fitting a logistic regression to data with a high number of predictor variables). Every ...
154 views

### Classification trees to pick predictive variables

Running a logistic regression we get p-values for all the input variables which helps us choose significant inputs. Similarly can we use the classification trees to pick variables that are split, and ...
242 views

### Logistic regression is slow

I am relatively new to machine learning and I have a data classification problem where each sample has ~1500 features (continuous) and the category is binary. I want to apply logistic regression, for ...
1k views

### Logistic regression on categorical data

I have large dataset (around 2 million records and 300 features) with a lot of missing data. Most of the independent variables are categorical (some of these variables have more than 40 valid values). ...
134 views

### Are there popular dimensionality reduction tools for classification type supervised learning?

I am familiar with PCA as a linear transformation in order to align the axis of the IV space with the directions of maximal variance in order to possibly be able to reduce the dimensionality of the ...
497 views

### Maximum entropy classifier and sentiment analysis

I am doing a project work in sentiment analysis (on Twitter data) using machine learning approach. In order to find the 'best' way to this I have experimented with naive Bayesian and maximum entropy ...
126 views

### Remove duplicates from training set for classification

Let us say I have a bunch of rows for a classification problem: $$X_1, ... X_N, Y$$ Where $X_1, ..., X_N$ are the features/predictors and $Y$ is the class the row’s feature combination belongs to. ...
865 views

### How to interpret result for MultiModelByRegression in RapidMiner?

I couldn't find any information in the documentation of rapidminer. I have a data set with the following attributes: a,b,c,d,e. The types are: ...
202 views

### Options for comparing logistic regression models

I want to choose variables for building a logistic regression model by comparing the GOF of different types. The problem is that some of the candidates have some missing values so I can´t use the ...
153 views

### Logical extensions after logistic regression

I have a number of predictors to use for a binary (Classes 0 and 1) classification task. Let us call them $x_1, x_2, x_3, ... x_n$. The way these are calculated, my naive heuristic assumption is that ...
117 views

### Constrain decision boundary to fall on grid lines in multiple class logistic regression

I would like to use multiple class logistic regression to learn the decision boundaries separating the different classes (denoted by color) in the image below. Kernel logistic regression with a RBF ...
500 views

### Comparing logistic regression models

I have a 2(truthfulness) x 2 (immediate test) study where I am looking to compare 2 logistic regression models. Both are classifying the same outcome variable: truthfulness (truthful versus ...
614 views

### Are Fisher's linear discriminant and logistic regression classifier related?

I have some experience with both FLD and LR for classification. On most data sets, I get very similar results, which raises the question - are FLD and LR related in some why? An idea, for example, ...
242 views

### Logistic regression with non-negative parameter

I want to model the probability of a binary variable x given some predictor, d. It needs two parameters: One parameter that sets the "break point", at which p(x=1 | d) = 0.5. One parameter that ...