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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14 views

Good metric to distinguish between fat tailed and narrow distribution

Could anyone point me to a good metric to distinguish between the following distributions? One distribution seems to be exponential type whereas the other is fatter and sometimes also has a peak ...
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18 views

What is the relationship between vector space models & support vector machines?

Is there a relation between them? Specifically, if I have a VSM can I classify it through SVM?
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11 views

classify with 3 class [on hold]

How do I calculate average rate error using Bayes and neural network classification, for example, on the three classes in Fisher's iris data?
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0answers
14 views

Graphically, how does the non-linear activation function project the input onto the classification space?

I am finding a very hard time to visualize how the activation function actually manages to classify non-linearly separable training data sets. Why does the activation function (e.g tanh function) ...
2
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2answers
138 views

When can a continuous variable be treated as categorical?

I have a continuous variable, which can take any value between 0 and some large, though not infinite, number. Let us assume that the maximum possible value is 1000. The values are nowhere near ...
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0answers
5 views

Bi-normal separation feature selection (BNS) in R

I'm doing binary classification on highly dimensional text data, with a biased class distribution. After reading this paper, i found out about BNS feature selection. Is there any package that ...
2
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0answers
20 views

R programming, correlation of quantitave variables with one qualitative variable

I have a flat CSV file that has one column of student names, one column of grades (outcomes) coded as a factor A-F, and about 100 columns of test scores (independent variables) of various sorts, on ...
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23 views

Accuracy low if test data belong to a single class

For my classification task I have two classes labeled 0 and 1. I am using Random Forests from sklearn package in python. I have two files for different classes. So I loaded the files, combined them ...
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2answers
33 views

Handle missing values in factor variable

I have a huge dataset for a binary classification problem (about 1.5 million rows), and the feature space is quite large (145 dimension). Some of these features are factors (YES, NO), but there is ...
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0answers
11 views

Make a classification dataset with binary features using scikit-learn

I would like to illustrate a classification algorithm by using this algorithm on a 2-class dataset with binary n-dimensional features. In the past, I have used the scikit function make_classification ...
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0answers
64 views

Any advice on how to improve my accuracy rate in text classification?

I'm trying to do a text classification task. Here are some specs: Context file size = 1M+ documents already labeled Number of top-labels = 17 Number of sub-labels = around 130 Each document is ...
1
vote
1answer
69 views

Which PCA (or kernel PCA) basis better describes a single test sample?

I have two PCA bases obtained by decomposition of two groups of training data. I also have some samples of test data. How can I decide which PCA basis fits better each test sample? I tried to ...
1
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1answer
45 views

Probability to Likelihood

I have a problem on calculating the likelihood of observing a data point x given the predicted lable. My application is on text classification where I have to detect Spam and No Spam documents. I ...
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0answers
8 views

Binary classification with KNN

I post here because I don't know how to improve the performance of my binary KNN. The problem is that I have 99.8% Specificity and only 82% Sensitivity, but I'd rather have more Sensitivity than ...
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1answer
31 views

Random Forest confusion matrix

I've been creating some random forest models using the caret package in R. I don't have a large amount of data to work with so I'm using 10 x 10-fold CV in lieu of an independent test set. When I ...
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0answers
16 views

When would Probabilistic Graphical Model be more useful compared to other commonly used models?

When would PGMs be better compared to other classification algos like DT, or LR? I see that it will be better if there are relationships / dependencies between the features. Are there any other ...
2
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0answers
14 views

soft training and classification (class membership)

there are several soft classifiers in r, such as linear discriminant analysis. Functions such as lda {MASS} show the likelihood of each case being classified to belong to each of the classes defined ...
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23 views

Prediction for new data using trained Gaussian Mixture Model

I am not sure how to do the prediction for some new data using trained Gaussian Mixture Model (GMM). For example, I have got some labelled data drawn from 3 different classes (clusters). For each ...
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14 views

binary classifiers and linear classifiers

I'm a newcomer in the field of machine learning,and my interest is keyphrse extraction using machine learning methods. 1.i need to know differences and similarities between binary classifiers and ...
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3answers
40 views

Is kNN best for classification?

I wanted to know if kNN might produce the best result for classification? Since, it is not model based, it does not loose any detail and compares every training sample to give the prediction. Hence ...
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2answers
54 views

Classifying by performing PCA for positive and negative datasets separately

I have a dataset with binary labels, and I try to figure out whether the data can be classified and yield the ground-truth labels. I thought to try PCA for the data with each of the labels, and see ...
2
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2answers
62 views

Why does the scaling of feature vectors improve performance of SVM classifier?

I've found that performing scaling in SVM problems really improves the performance of SVM ... But I don't understand why! I have read this explanation: "The main advantage of scaling is to avoid ...
1
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0answers
30 views

How can I make sure that an LDA implementation works?

I am currently experimenting with neural nets for classification of on-line handwritten data (hence: not pixels, but time series data). To do so, I use several toolkits (internal development of my ...
2
votes
1answer
54 views

Can someone explain to me the Bayesian classification model?

I often read about converting from a normal classification model like logistic regression and then using an equivalent Bayesian model. As I understood, it's somehow the same model but with a different ...
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2answers
21 views

Supervised classification using tree methods

What work has been done for supervised classification using tree methods that utilize linear combinations of variables instead of single variables?
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12 views

Importance of class frequency in classification

Suppose we are classifying instances into n classes that, in practice, occur at frequencies p1, p2, ... pn, (for example classifying news-articles as one of n different topics). For the purposes of ...
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9 views

How we can statistically compare performance of two models before and after outlier detection?

As you know we can use Mcnemar's test to compare performance of two models in binary classification problem. But in my case i ...
1
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1answer
129 views

scikit multi label classification

I am trying to classify data into four different labels. The training data looks something like: ...
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0answers
20 views

Two tails or one tail McNemar's test in a binary classification problem. Which one should i choose?

I'm using McNemar's test for compare two designed models in a binary classification problem. As you know we have two kinds of this test. ...
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0answers
21 views

Stochastic Gradient Descent Validation

I am trying to implement Stochastic Gradient Descent algorithm using Gaussian basis functions. The equation I am trying to implement is as follows: $$ w \gets w + \alpha (y_t - w^T\Phi(x_t)) ...
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1answer
46 views

CHAID decision tree - Binning continuous variables

I am running a CHAID classification tree on SPSS to classify my data set. I have a couple independent variables including categorical and continuous ones. For continuous variables, I've noticed that ...
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0answers
9 views

How to classify test objects?

I'm coding a program that tests several classifiers over a database weather.arff, I found rules below, I want classify test objects. I do not understand how the classification, it is described: "In ...
0
votes
1answer
48 views

How to use k-fold cross validation in naive bayes classifier?

I'm trying to classify text using naive bayes classifier, and also want to use k-fold cross validation to validate the result of classification. But I'm still confused how to use the k-fold cross ...
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0answers
6 views

How to define my custom cost function to be used in (stochastic) gradient descent?

I have a text classification problem were the classes are 20 cities and the input is text Bag of word features. I am using Logistic Regression and my cost function is negative log likelihood: ...
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0answers
12 views

Experiment design: classifying 3 classes (2 easy, 1 hard)

Bit of background: I have a problem of classification of 3 classes. Given the training set (80%) and a held-out set (20%), I found out that 2 classes are easy to discriminate/classify. The third class ...
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0answers
27 views

Neural Networks sigmoid activation with bias updates

I am trying to figure out if I am creating an artificial neural network using the sigmoid activation function and using bias correctly. I want one bias node to input to all hidden nodes with static ...
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0answers
6 views

Detecting false positives of a classification algorithm

I run a web service with a lot of users. Some of these users are involved in undesirable behavior (e.g. trolling). I've come up with a classification algorithm to detect these users (and deactivate ...
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0answers
19 views

Regression/classification, how to accommodate the missing columns of data?

I would like to apply any regression methods, such as the ones available using WEKA libraries (for example, SVMs, NNs, Random Trees,...) . However, I am getting very low results since I am missing the ...
0
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0answers
31 views

What is the next step after acquiring the parameters(means, covar, priors) from GMM via EM

I am comparing the results achieved from clustering via K-means and GMM. For comparison I have accumulated a dataset of images. The training set consists of 359 images. I used SIFT to extract the ...
0
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0answers
14 views

How to use Similarity Measure in K-nearest neighbor Classification?

I have a similarity measure just like cosine. How can i use that similarity measure in traditional k-nn classification? Please provide some literature review (research papers) details which i should ...
2
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2answers
50 views

Feature Selection: Information Gain VS Mutual Information

Setting: Multi-class classification problem with discrete nominal features. There are many references mentioning the use of IG(Information Gain) and ...
1
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2answers
34 views

Classes distribution in training set

In my actual data class A has 90%, class B has 9% and class C has 1% (numbers are made up for sake of simplicity). Now I want to prepare a training set for my classifier (I plan to use Vowpal Wabbit). ...
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0answers
20 views

unary classification in PyBrain

I've just started using PyBrain for some data classification work, and I've gotten it working pretty well where I have data from all possible classes and I can train the network using all the classes. ...
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2answers
37 views

Suitabiility of the confidence score generated by SVM as a proxy for membership function

SVMs can generate a confidence score which is basically like a probability for a particular data item to belong to the particular class. I want to use this probability as a proxy for the 'distance' of ...
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0answers
14 views

How to split a class which is not very cohesive?

Using the silhouette width metric I can find out as to how well each object lies within its class after classification is done. I next find the average silhouette width of objects within a class and ...
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0answers
6 views

Almost constant Target variable

I am building a classification model and my target which is dichotomous is close to 95% 0 and 5% 1. Is there any rule or guidelines/assumptions that I should follow for an almost constant target ...
1
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2answers
79 views

Semantics rules? A classification challenge

Suppose we make interviews on a large number of households in which we ask, among other things, the sex and age of the individuals living in the household, and also who among these individuals is the ...
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0answers
9 views

Analytical or explicit solution for optimal threshold of a simple classifier?

Given a training sample $\{(x_i, y_i): y_i \in \{-1,1\}, x_i \in \mathbb R, i=1,\dots, n\}$, construct a classifier $f_t, t \in \mathbb R,$ of the form $f_t(x) = 1$, if $x \geq t$, and $f(x)=-1$, if ...
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0answers
19 views

Combined Two CLassifiers

I am involved in a research where i need to classify group of words (strings) into two classes I am currently reached a dead point where my classifier is not doing as i expected. I used like three of ...
1
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3answers
85 views

regression for binary classification

Given a binary classification problem, is there any inherent difference (or advantage) to using a classifier (say a logistic regression) and a regression, where the classes are denoted by 0 and 1 (or ...