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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Interpreting the lift curve

Suppose we have two classes: A and B. Suppose we use a logistic regression to assign each unit to A or B. The curve lift is calculated through this formula: $\frac{n_{22}/n_{.2}}{n_{2.}/n_{..}}$ ...
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1answer
20 views

Statistical test for classification models

I have 3 models from which, for each model, I train a classifier and then evaluate it, currently using stratified 10-fold cross validation and then take the mean accuracy ratio of these from each ...
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1answer
14 views

Pruning Conditional Inference Trees

I am trying to build a prediction model using classification trees. While I tried the "rpart" package, the results were not entirely satisfactory. Hence, I thought of exploring conditional inference ...
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0answers
15 views

Is it possible to explain the performance of a classifier by the specific properties of a data set?

I receive the following comment from a reviewer : "I think that the authors could explain in more details the results. For instance, there is no discussion linking the specific properties of the ...
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1answer
34 views

Is building training data set from unlabeled data considered as a scientific contribution? [on hold]

Is building a training data set, from unlabeled data, for a machine learning classifier considered as a scientific contribution?
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0answers
14 views

Classifying colors based on prior knowledge of what the colors will be

I'm trying to think of a way to classify a set of observed pixel values based on prior knowledge. I'm projecting an image with a set of known colored ordered vertical stripes (say a red stripe, a ...
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1answer
11 views

Clarification on using train vs glm vs rpart for classification problems in R

I am using the glm function in R to perform logistic regression. I converted the outcome variable to a numeric between 0 <=y <= 1 as follows ...
6
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1answer
66 views

Bag-of-Words for Text Classification: Why not just use word frequencies instead of TFIDF?

A common approach to text classification is to train a classifier off of a 'bag-of-words'. The user takes the text to be classified and counts the frequencies of the words in each object, followed by ...
2
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0answers
25 views

Class probabilities in Neural networks

I use the caret package with multi-layer perception. My dataset consists of a labelled output value, which can be either A,B or C. The input vector consists of 4 ...
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2answers
48 views

Odds vs probability in logistic regression

I am going through Trevor Hastie's Classification Techniques. Its says Odds are traditionally used instead of probabilities in horse-racing. I still don't understand how they relate more ...
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0answers
16 views

Describing the distribution of N points in D-dimensional space?

I want to tackle a classification problem by describing the samples as its descriptors' distributions. So let's say each sample has a label, and $N$ vectors of dimension $D$, (N and D are fixed) and ...
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0answers
12 views

3D Zernike moments vs. Spherical Harmonics. Which one has higher discriminative power as shape descriptor?

I am looking for a comprehensive study that has performed comparison of different 3D shape descriptors for classification/clustering problems. Particularly, I am interested in 3D Zernike moments vs. ...
2
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0answers
40 views
+50

Incorporate new unlabeled data into classifier trained on a small set of labeled data

I have a set of 400 labeled samples (8 numeric features) on which I trained a binary classifier. The problem I am facing is that once the classifier is shipped to the users, I will get additional ...
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0answers
28 views

Which unsupervised learning method should I use on classification on many point cloud datasets?

I have a few abstract and high dimensional point clouds in the form of distance matrices. I want to do unsupervised learning on this dataset. The problem is, I am not using one distance matrix, but ...
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0answers
16 views

Integrated Classification Likelihood computation for R package HDclassif

I'm in the process of fitting some mixture models to some data I have. As this data is high-dimensional, I used the subspace clustering package HDclassif. As the package has no option for the Akaike ...
5
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1answer
72 views

Where must we use Bagging or Boosting?

I want to know when Bagging is better than Boosting? How I select appropriate method for my classification task? I think when we have many outliers in our data-set, Bagging must be better than ...
0
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1answer
22 views

What is the best measure for unbalanced multi-class classification problem?

What are some possible classification metric for an unbalanced problem ? Due to skeweness of the distribution, accuracy value is not so meaningful. For instance, if I predict all the classes to class ...
2
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1answer
75 views

How can using Logistic Regression without regularization be better?

I'm using this Java machine learning library: https://sites.google.com/site/qianmingjie/home/toolkits/laml From the library I'm using Logistic Regression: ...
1
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1answer
48 views

Can we express logistic loss minimization as a maximum likelihood problem?

I have a simple question about the equivalence of loss minimization and likelihood maximization for logistic regression. Say are given some data $(x_i,y_i) \text{ for } ~i = 1,\ldots,N$ where $x_i ...
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1answer
8 views

GPML producing wrong output using correct target labels

I am using the GPML code found here. The key function in the aforementioned library is the gp function described below: Two modes are possible: training or ...
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0answers
8 views

Is there any lower limit for number of positives when generating lift plot?

I am wondering if there is any condition on number of positives in test set when I am trying to compute lift plot to check the properties of my classifier?
2
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0answers
45 views

Isn't caret SVM classification wrong when class probabilities are included?

*Please note this question is about the Platt probabilistic output and SVM class assignment, not about the code or the package itself. It just happens to be the code where I stumbled on the issue. In ...
1
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2answers
36 views

Binary classification when one class consists of multiple subclasses

I have the situation where I want to distinguish between two classes $C_1$ and $C_2$, where $C_2$ consists of three different types of subclasses $C_{2,1}$, $C_{2,2}$ and $C_{2,3}$. Also, it is easy ...
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0answers
8 views

declare class label in classifier with only X field in r

I have a simple problem: I can do SVM classification with some packages but have problem with others. let's say: my data set for training= ds and for testing ...
2
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3answers
64 views

Criteria for classification performance

In binary classification, are there criteria or guidelines available to judge if classification performance of the testset (unseen data) is poor, medium or high? I realise that this may depend on ...
3
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3answers
355 views

KNN: 1-nearest neighbor

My question is about the 1-nearest neighbor classifier and is about a statement made in the excellent book The Elements of Statistical Learning, by Hastie, Tibshirani and Friedman. The statement is ...
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0answers
40 views

How to make correlated variables, uncorrelated?

I have 7 independent variables with 3 observations and they are highly(<95) correlated with each other (each of them) and my dependent variable is head count for 3 years( thus only 3 observations ) ...
5
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1answer
178 views

Is it feasible to transform each variable differently while doing multiple regression

I have a dataset with 10 variables ...is it feasible to transform each variable differently while doing multiple regression... for example new_V1 = log(v1) New_V2= V2^2 New_V3= 1/V3 Likewise ...
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1answer
22 views

How to classify samples with different features?

Assuming we are considering following classification problem: We have a dataset containing the time when a user call a taxi in one day, but different users call the taxi different times. For example: ...
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1answer
11 views

Classifier for weighted class label

Is there any rule-based classifier which be able to classify samples with weighted class labels. In other word, different confidence in tagging samples. My problem deals with learning samples from ...
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0answers
8 views

Supervised Classification of one element in each Set

Suppose I have the following supervised classification problem. Given some list of sets X, where $$ X[i] = S^{(i)} $$ and $$ S^{(i)} = \{X^{(i)}_1, \ldots X^{(i)}_{L^{(i)}}\} \qquad \text{where } ...
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2answers
40 views

Using k-means for reducing the size of the training set of a Kernel SVM

I have a classification problem with the following characteristics: a few million data points around one hundred features non-linearly separable Training a SVM with an RBF Kernel is not feasible ...
0
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0answers
37 views

Which algorithm fits best to a transactional data classification problem?

I have transactional database - the data looks as follows: ID - COLUMN1 - COLUMN2 - COLUMN3 0 - A - B - C 0 - A - D - C 0 - E - B - C 1 - A - B - C 1 - A - B - C 2 - ...
3
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1answer
102 views

How to reduce number of false positives?

I'm trying to solve task called pedestrian detection and I train binary clasifer on two categories positives - people, negatives - background. I have dataset: number of positives= 3752 number of ...
2
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0answers
28 views

Anomaly Analysis (K-Means) - finding suspicious activities/operators

I am relativly new to the field of data mining and want to make a anomaly detection on transactional retail data. I want to use a simple anomaly detection (kmeans at the moment) for finding suspicious ...
1
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0answers
19 views

What is cross classification?

I could not find a Wikipedia page, can someone explain to a non-statistician what cross classification is? An example where this technique is used in financial risk assessment (credit risk / market ...
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0answers
54 views

How to combine weak classfiers to get a strong one?

Let as assume that we have a binary classification problem. We also have several classifiers. Instead of assigning a vector to a class (0 or 1) each classifier returns a probability that a given ...
0
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0answers
39 views

How to exploit relationships between independent variables?

Data: Each instance (representing a document) is a bag-of-entities (like BOW, except they're Wikipedia entities instead of words), so each feature is a binary or tfidf-like score based upon the ...
3
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0answers
44 views

Decision boundary in multivariate naive Bayes

This is from a sample exam for which I do not have the solutions. The question as stated is: True or False: The multivariate Gaussian naive Bayes always has a linear decision boundary. Explain ...
0
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1answer
41 views

SVM parameter tuning for unbalanced classes (with class weights)

I am trying to run an SVM on an imbalanced dataset (0-90%, 1-10%) using the e1071 package, with the radial kernel. I am using cross-validation to select the best gamma and cost. Additionally, I want ...
3
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1answer
71 views

What's the meaning of dimensionality and what is it for this data?

I'm doing my assignment for my "Modeling and Optimization" course, and now I have doubts on the first question: What is the dimensionality of the data? What are the min, median, max, mean, ...
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0answers
16 views

Radial Basis Function Networks for Classification

I'm thinking of implementing a radial basis function network for a multinomial classification problem. Is there any benefit to this over using gaussian mixture modeling? Are they essentially the same ...
1
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2answers
72 views

Classifer for unbalanced dataset?

Is there any classifer that can natively support unbalanced datasets? Or what best practices you can suggest to handle such datasets? For example I want to solve task called "pedestrian detection" ...
0
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0answers
8 views

Merging two different segmentation solutions into one

I have the following problem: two different segmentation analysis to do, one using needs/motivations for consuming a product and one related to general attitudes toward product category and lifestyle. ...
0
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1answer
39 views

Robust softmax solutions for Theano?

I am implementing multilayer perceptrons with the softmax activation function over Theano. In some extreme cases I am running into problems with too high/low values in the softmax function that ...
0
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2answers
17 views

Prediction of n class variables

I have a historical data that has discrete variables. Let say I have data points with class labels 1, 2,3,4,5. For a given classification problem, I can use the training data and then get the trained ...
0
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0answers
20 views

Map of activated brain regions for special feature extraction method

I have read the following paper: "Feature Extraction for fMRI-Based Human Brain Activity Recognition". The most useful point for me is the new method of extracting features from fMRI images. It ...
0
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0answers
22 views

set SVM parameter range values for tuning [duplicate]

I am newbie to using svm for classification. I want to tune svm parameters by .TrainAutofunction in EmguCV. But I don't know what are the range(min-max value) of below parameters that I should give to ...
1
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1answer
18 views

How to interpret concretely the misclassification error?

I'm reading about Cart classification with rpart on R, and after all we should compute the misclassification error, given that y is the column that stocks classes, and x is the variable columns and ...
3
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2answers
49 views

Does it make sense to generate prediction intervals for the estimates of a logistic regression?

Say I have a binary outcome of 0 or 1 and suppose I were to use logistic regression model to estimate the probability a new sample will have an outcome of 1. I have read answers (for example here: ...