Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a ...

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Logistic regressions questions about line fitting vs. probabilistic interperetation

Suppose I have data points $(x_1^1, x_2^1), (x_1^2, x_2^2), (x_1^3, x_2^3), \ldots$ in $\mathbf{R}^2$ that fall in one of two classes, $y^i=0$ or $y^i=1$. I can find a linear separator for these ...
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17 views

Classify streaming, partially complete data into groups defined by prior clustering

Suppose I have M observation vectors, offline, $y_t$, $ t =1 ... M$, and each observation is $n$ dimensional. I then cluster these observations into $k$ clusters. For computing the clustering ...
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2answers
22 views

A good description of the random forests method

Can anyone suggest a good book or article describing the random forests method of classification? I'm not satisfied with the way the subject is treated in "An Introduction to Statistical Learning with ...
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9 views

Data complexity measure which affect classifier performance

As we strive to explain accuracy of machine learning algorithms, many authors suggest to start by degree of complexity in data. I am working in data complexity measure like: class ...
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4 views

Micro vs weighted F1 score

In a multi-label or multi-class classification setting, when choosing between a micro or a weighted F1 score, what shall I take into account? The main upside of choosing macro is that one gets a ...
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28 views

How LDA, a classification technique, also serves as dimensionality reduction technique like PCA

In this article , the author links linear discriminant analysis (LDA) to principal component analysis (PCA). With my limited knowledge, I am not able to follow how LDA can be somewhat similar to PCA. ...
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8 views

Prediction using r mlogit: How to reproduce “Frequencies of alternatives” from model summary

I am trying to reproduce results in Train & Croissant's vignette "Kenneth Train’s exercises using the mlogit package for R." Specifically, Train illustrates multinomial-logistic regression using a ...
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12 views

decision tree question in spss

I have a question related to decision tree making in SPSS. My dependent variable is categorical (people with hypertension and without hypertension). The predictors are scale variables like systolic ...
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1answer
38 views

Classification problem where one attribute is a vector

Hello I am a layman trying to analyze game data from League of Legends, specifically looking at predicting the win rate for a given champion given an item build. Outline A player can own up to 6 ...
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17 views

Is there a classification model with possibility to set transition probabilities for each sample?

There are models where we can to set initial transition probabilities between classes like Markov models. But what if we need to change the probabilities dynamically depends on all previous ...
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20 views

Why is my simple implementation of sub-gradient descent for SVM not converging?

As an exercise in understanding the mechanics of the Support Vector Machine, I am attempting to implement the SVM myself, in Python. I'm more concerned with understanding than efficiency, so I wish to ...
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1answer
28 views

MSE vs area under ROC

I'm testing the performance of two binary classifiers on a simulated dataset. I'm seeing that classifier 1 has a higher MSE (mean squared error / classification error) than classifier 2, but ...
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13 views

Multi-tier classification

First of all, I'm not sure wether the question title is correct, but I'm facing a puzzling problem. Please point me to the correct term and some relevant literature. This is the problem: Let's say I ...
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0answers
16 views

What is it called when the Test Set and Training set is the same?

Normally when evaluating a model, the training data is split into a test set and a training set. I want to evaluate the best possible performance of the classifier on my task. So I have Trained it ...
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0answers
7 views

Training a classifier to find a subset of some data

I have a dataset of individuals which can be split into two groups: those that have performed an action (group 1) and those that haven't (group 0). For each individual I have a large number of ...
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0answers
14 views

Predicting lat/long from binary features

I have a number of observations that occur around my city (a small area), and several of them have latitude and longitude. I have been looking into predicting the latitude/longitude of the ...
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1answer
37 views

Machine Learning: What are the types of data set?

Is there a classification of the type of data sets in machine learning problems? I am specifically interested in classification problems. I know a large number of algorithms like SVM, NN, Decision ...
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1answer
9 views

Building a multilabel classifier for text

I am given a number of short texts (very likely to be shorter than 25 words). The specificity of the short texts is that it can (logically) belong to one or multiple categories. For example: ...
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1answer
28 views

How to report confusion matrix of Random Forest classifier on test set using R? [closed]

First of all, I have to say that I'm newbie in working with R. Anyway, I'm going to apply Random Forest classifier on my data set using R. To do this, I beforehand divided my data set into training ...
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16 views

Existing relationship between predictors and response in a classification method

Lets say that there are 3 predictors A,B and C. There is a response Y, which is already related to A,B and C mathematically. Y = ABC. Past data for Y does not exist, and is calculated using the above ...
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1answer
27 views

Can a variable become statistically significant after the addition of another variable? [duplicate]

I am doing forward stepwise logistic regression. I have heard that its common for a previously statistically significant variable to become not statistically significant when one or more variables are ...
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1answer
29 views

Binary classification: positive and negative event

Let's consider a binary supervised classification problem. Be "A" and "B" the two classes. Sometimes it is said that it if an individual belongs to one of the two classes, we have a "positive event" ...
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1answer
24 views

Logistic regression with categorical predictors

I'm trying to play around with classification models and started off with logistic regression in R. When I have all the numeric variables in the data set the model works correctly and I was able to ...
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15 views

Logistic Regression: Classification Table, Sensitivity and Specificity

I'm currently working with binary logistic regression in SAS to predict the probability of loan default and I have a problem with sensitivity and specificity. I have a data sample of about N=3650 ...
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12 views

Finding influential characteristics in a chain of events

I have some data which is sequences of actions performed by individuals. All of these actions have properties (some catagorical, some binary, some continuous numeric). Individuals can have 1 to ...
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10 views

calibration of model using true positive rates for low frequency classess

I am conducting a classification problem on a very low frequency class. For example there just 20 samples in 1,000 samples which should be classified from other. I get very high accuracy but not ...
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1answer
25 views

Is there any clearer term than multiclass classification?

Multiclass classification is the problem of classifying instances into one of the more than two classes. However, the prefix multi means "more than one" (as in multi-label classification: if one ...
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4 views

Recognizing types of people on a CDR data set

I have 2 month of call detail record of people in my country. Each record has a user id, lon/lat location, and datetime. Some (About 1/4) users are classified as class A/B. by the mobility patterns I ...
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11 views

how to calculate separation index value in PCA and KPCA

i have problem on calculating separation index (SI) in PCA and KPCA, i have been calculated pca and kpca and got the percentage of variance from PC1 and PC2. Is it same if I use percentage variance or ...
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1answer
17 views

Evaluation of binary approach to one vs all multi-class classification

I'm working on a multi-class problem which I have redefined as a series of binary problems (i.e. a one vs all classification problem). However, each observation can belong to more than one class. For ...
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13 views

How can you use a decision tree classifier on nested data?

I have a data model with natural one-to-many relationships. ...
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0answers
6 views

How to fill in the missing labels which have more than 1500 levels

I have a question regarding "classification". I have a data set with the target label of more than 1500 nominal categories (there is no way to bucket them as they are just individual strings). The ...
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0answers
21 views

Relationship between Matthews correlation coefficient (MCC) and the Pearson's Chi-square

I would like to find a reference showing that the MCC follows a Chi-square distribution. This is suggested in this wiki: https://en.wikipedia.org/wiki/Matthews_correlation_coefficient, as they claim ...
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1answer
24 views

Using SVM when kernel is simple and sample size is large

Consider SVM classification: $y_i \in \{+1,-1\} $ are labels, $\mathbf{x}_i$ are covariates ($i=1\ldots N$). Let $K(\cdot,\cdot)$ be the kernel function, whose corresponding feature mapping is ...
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1answer
13 views

How to do pair wise classification?

I would like to know how to do a pairwise classification. I have 3 classes A,B and C. I have samples for each class. Now I would like to build a classifier in such a way that given a new test sample, ...
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21 views

Compute the Gibbs energy

I have a question about Gibbs distribution in Stochastic theory. In which, it defined a clique as a a subset $C$ in the whole image $\Omega$ if two different element of $C$ are neighbors. Figure 2 ...
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1answer
24 views

Getting distance of points from decision boundary with linear SVM?

I posted this originally in Stack Overflow but realize it might be more of a statistics question. I am using SKLearn to run SVC on my data. ...
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0answers
59 views

New rare-event regression method somewhere between logistic and survival

I keep running into situations (in my job) where I need to predict relatively rare events that occur at most once per entity, across many entities, and over time (e.g. predicting mortality of cancer ...
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1answer
18 views

Understanding the One-Vs-The-Rest classifier

Introduction I am working on a multiclass classification problem by using the One-Vs-The-Rest classifier. I want to check if my understanding of the classifier is correct. The ...
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0answers
5 views

Evaluation metric and Class Imbalance in Label Propagation

I'm using the MAD Label Propagation algorithm as described in the following paper "New Regularized Algorithms for Transductive Learning" by Partha Pratim Talukdar and Koby Crammer ...
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1answer
24 views

Confidence interval for expected prediction error from cross-validation

I am using a support vector machine for binary classification on a sample of size 150 (75 of each class). I am using 5-fold stratified cross-validation to estimate the expected prediction error, i.e. ...
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2answers
14 views

How to compare 2 classifers using confusion matrix?

How to compare 2 classifers using confusion matrix? For example if we have 2 confusion matrix(binary classification) obtained from different classifers or using different features, how I can compare ...
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1answer
28 views

Methods to reduce the number of class labels

I have a dataset with 17 classes which will be predicted using a classification algorithm (QDA, Decision Tree or something similar) using between 2-4 features. Many of these classes have significant ...
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1answer
36 views

Which standard error formula for the area under the ROC curve should I use

I am trying to assess the performance of a procedure in identifying something abnormal in the cities of a particular state in USA. I tested this procedure on six different cities with different ...
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0answers
25 views

How to use chi-squared statistics to select features in multi-class classification in R

I have 50k text records which has almost 20k features and 19 class labels. I want to do a multi-class classification in R. I know that for a binary classification, the table and formula below are the ...
0
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1answer
47 views

K-fold repeated cross validation for classification accuracy in Caret

I am new to cross-validation and I have a data-set called LDA.scores for 12 measured call-type parameters. I am trying to run a k-fold repeated cross validation with 10 folds and associated naive ...
3
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0answers
28 views

What are the votes in R's unsupervised random Forest?

I’m trying to better understand unsupervised random forests. An important part of understanding unsupervised random forests is being able to assess how good / appropriate a given forest is. For ...
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0answers
14 views

On which kind of problems preprocessing data using RBMs (unsupervised) could give an edge?

I am new to machine learning and basically so far I've been using only supervised algorithms, however, recently I started to use RBMs in combination with some classifier (using a pipeline in scikit ...
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2answers
23 views

Are Decision Function and Separating Hyperplane the same?

In many machine learning algorithms such as SVM, GBM, Logistic Regression, etc., are Decision Function and Separating Hyperplane the same?
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1answer
26 views

What should the AUROC be on the test set when no positive example is present?

Assume we have a probabilistic, binary classifier. We compute the AUROC on a test set in which no positive example is present (i.e. the ground truth is always 0). What should the AUROC be?