Tagged Questions

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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28 views

When normalization is counter-productive

Could you give me general examples of when normalization is not used properly and affects badly the classification accuracy, or when it is not needed?
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0answers
13 views

Should I assign numeric values to classes?

I was reading a paper and there was a dataset with 3 distinct classes. So, he assigned 0, 0.5 and 1, respectively to the classes. He used SVR. Then he used a method to find thresholds so it can assign ...
0
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0answers
23 views

Mix of two bivariate distributions (two correlations hidden in data)

We have two metric (continuous) variables, say $X$ and $Y$ and are interested in a correlation between $X$ an $Y$. Actually, a correlation test (Pearson or Spearman) is not significant, i.e. it does ...
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1answer
18 views

unsupervised clustering with “unclassified” items

I have data (some behavioral features, measured on some scales) on people. I want to cluster people based on these features. This is an unsupervised scenario, as I have no prior knowledge on the ...
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0answers
20 views

Sufficient data volume for inference

This question was probably discussed before but I failed to find it here. Let's say I have a medical data which contain some biomarker measurements for cases (patients with disease) and controls ...
0
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1answer
16 views

Which Machine Learning algorithm: Sorted list of tags given metadata?

Our system allows an admin to manage a database of university courses. These courses have multiple fields, like the department, a title, and a description. I am adding the ability to add learning ...
4
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1answer
74 views

Unintuitive interpretation of probabilities when doing logistic regression

The observations in my dataset can be split in two classes. The observations in class 1 are for sure correctly labeled. The observations that has been designated to class 2 have a huge percentage of ...
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0answers
28 views

How to transform test set to the training set transformed space with PCA?

I'm working on a text classification project, and I want to reduce the tf-idf matrix dimension with Principal Component Analysis (PCA) and then train my model with this, which is pretty ...
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0answers
33 views

Caret feature selection with customized random forest classifier

I'm following the Caret package tutorial for constructing customized functions for a recursive feature elimination. I can reproduce the provided example which is a random forest regression. However, ...
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0answers
20 views

What metric can I use to indicate if a class should be split?

I have trained a classifier based on some training data. Now, when I add test data consider the possibility the datapoints do not strongly belong to a class. So much so, that it would make sense to ...
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0answers
32 views

How to calculate classification accuracy? [closed]

I have Train and Test data, how to calculate classification accuracy with confusion matrix ? Thanks ...
0
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0answers
5 views

Precision in a multi-label classification when empty set is predicted

As we know, for a test instance, the precision of a prediction is defined as |T intersect P|/|P|, where T is the true set of labels and P the predicted one. Then what is the precision when P is ...
0
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0answers
10 views

How do I install and use Shogun toolbox in matlab? [closed]

I want to use Shogun toolbox in matlab (windows) but their installation guide is not clear. Does anyone know simple steps to install shogun toolbox in matlab?
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1answer
33 views

Multi Output Neural Networks

Up until know I only used neural networks to classify a single output, I set one output neuron for each class and check which neuron has the highest/lowest activation. What I am trying to do is to ...
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1answer
24 views

Convolutional neural network with non-image input data

Can CNNs be used with input data which is not an image? The reason I'm asking is because the original image is often clipped in size because of border effects when doing the convolution. But if the ...
-1
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0answers
14 views

How to create a feature vector with scikit-learn? [closed]

I have extracted some bigrams from a corpus, how can i create a feature vector with those bigrams with scikit-learn?, could anybody provide me some example?. Thanks
1
vote
1answer
53 views
+50

cross-validation to predict distribution of errors on finite test sets

In one use of k-fold cross-validation for evaluating classifiers, one trains k models, each on n(k-1)/k examples, and tests each on n/k examples. The average accuracy on those k test sets of size n/k ...
4
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1answer
39 views
+50

How to measure when error stabilizes (convergence) on Random Forests (or, when do I stop training)

I'm doing an implementation of Random Forests. As I was the original paper (page 11) and this nice book on the subject (15.3.1, page 592), they mention that when the out-of-bags error stabilizes (when ...
1
vote
1answer
38 views

What is considered to be “good” classification rate?

Let's say I am trying to figure out whether two classes can be differentiated. My methods may not be perfect, but I would like to know whether my features "mean" anything that may possibly be added to ...
0
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1answer
39 views

Range of predicted probabilities by logistic regression

I have a binary classification problem with unbalanced classes, e.g. I have 500 examples of negative class(0) and 20 examples of positive class (1) and I need to estimate the probability of positive ...
0
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0answers
9 views

klaR package and the stepclass function

(R studio) Hi, I'm running LDA on a dataset with 250,000 observations, 2 classes and 30 variables. My goal is to create a classification model using the LDA function. After loading my variables I ...
0
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0answers
19 views

Good way to categorize count data?

I want to use some count data to train a classifier. The count data range from 0 to 400 something. There are a bunch of smaller counts (0's and 1's). I wonder what would be a good way to categorize it ...
0
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0answers
15 views

Regarding Naive Bayes and conditional independence

We all have been talking about how Naive Bayes may, in some cases, not perform well due to the fact that this assumes conditional independence of features and MOSTLY, this is not true for real world ...
0
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0answers
31 views

Multivariate regression with categorical response variables

Explanation of Data: I started with a data set where each user belong a specific group and their contribution to different domains. After multiple pivots and pre-processing attempts, I got my data in ...
0
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2answers
25 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 ...
1
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0answers
26 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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0answers
17 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
votes
2answers
157 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 ...
0
votes
0answers
11 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
votes
0answers
24 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 ...
0
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0answers
25 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 ...
1
vote
2answers
40 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 ...
0
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0answers
18 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 ...
1
vote
0answers
70 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
73 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
vote
1answer
47 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 ...
0
votes
0answers
13 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 ...
0
votes
1answer
55 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 ...
0
votes
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 ...
0
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0answers
37 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 ...
-2
votes
0answers
15 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 ...
0
votes
3answers
46 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 ...
3
votes
2answers
56 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
votes
2answers
67 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
vote
0answers
31 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 ...
1
vote
2answers
22 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?
0
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0answers
13 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 ...
0
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0answers
14 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 ...