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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22 views

Which type neural networks for time series classification

I would like to use neural networks to classification of time series ( I have some Patterns and I want to adjust input time series to an appropriate class) -ist it possible to do this job with ...
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11 views

prediction from incomplete observations

Suppose I have a linear model predicting class-membership from a set of predictors. Now, I am going to classify a new observation which has, however, some predictor values missing. How can I deal with ...
2
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32 views

Converting log odds coefficients to probabilities

Suppose we've ran a logistic regression on some data where all predictors are nominal. With dummy coding the coefficients are ratios of log odds to the reference levels. A colleague claims that we can ...
2
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26 views

Why linear transformation can improve classification accuracy when the dimensionality of data is high?

Let $X$ be an $m\times n$ ($m$: number of records, and $n$: number of attributes) dataset. When the number of attributes $n$ is large and the dataset $X$ is noisy, classification gets more ...
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12 views

Probability of outputs of binary classification in MATLAB

I have a binary classification problem and using neural network and SVM for it. So I choose a threshold (for instance, 0.5) for output of neural network. If output is greater than 0.5 it belongs to ...
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2answers
41 views

How to estimate confidence level for SVM or Random Forest?

I have two classes (say 1 and 0), and want to build a classifier. It is possible to use artificial neural networks (ANN) or any "real" classifying method such as SVM or Random Forest. In case of ANN, ...
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2answers
12 views

How to estimate confidence level for SVM or Random Forest?

I have two classes (say 1 and 0), and want to build a classifier. It is possible to use ...
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0answers
25 views

Best way to classify a set through a single feature

I need to classify a single dataset through a numeric value. I added below a simple dataset to explain what I need. Restriction: Category has two values: 1 or ...
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16 views

Reliability and Classification problem on real world educational data

I would need some advice on how to approach and model data coming from a real-world educational setting. Here is the basic design outline: Each student undergoes a series of "Practical Tasks" for ...
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11 views

How to normalize interaction terms?

I'm training a classifier for a supervised classification problem. Some of my features interact, how should I normalize these interaction terms? For example, if x1 and x2 interact, the interaction ...
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1answer
22 views

decision boundary of support vector machine when data is not linearly separable

Screenshot from this video: This describes the decision boundary of support vector machine as a optimization problem with two constraints. But it seems to assume that the data points are linearly ...
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2answers
45 views

How do we analyse likelihood in a dataset? [on hold]

I am working to analyze poverty rate using census data. I have a huge dataset. I want to extract the likelihood from this dataset in order to create patterns for energy consumption. What is the ...
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1answer
20 views

Some Basic things we need to do when we are doing text classification

I am working on a project where I have to do multi-label text classification. I want to understand that whether my approach is correct or I am missing something. I am using R to do it. Clean ...
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16 views

Classification measures for linear classifier

Let $\mathcal{H}\colon\mathbf{w}\cdot\mathbf{x}+b=0$ be a separating hyperplane, which some binary linear classifier results in. Let $\mathbf{x}_t$ be an unseen, new sample that appears and needs to ...
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14 views

How can I interpret the results of LSA?

I implemented LSA on MATLAB. I have a $D\times N$ term-document matrix, where $D$: # of words, $N$: # of docs. I did low-rank approximation using SVD, and got $$X_k = U_k \cdot S_k \cdot V_k' ...
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1answer
64 views

Finding an equation with many variables to fit a set of data

I am writing a program which takes notes from a keyboard as the input, (just numbers, 1 to 88) and decides which notes are played by which hand. There are a lot of variables, for example, the position ...
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22 views

How to subset alternatives in nested multinomial logistic regression?

I am trying to predict whether or not captains in a particular groundfish fishery choose to fish on any given day and what variables may influence that decision. Originally I had planned on using ...
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19 views

Why are Bayesian classifiers “robust to noise”?

In many different settings I've read that Bayesian classifiers like Naïve Bayes and Bayesian Networks are more robust to noise in the input data than other classifiers. I'm wondering what the evidence ...
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1answer
34 views

Classification Accuracy

I am classifying text based on news headlines and I am achieving accuracy up to approx 80%. I want to improve it more. But issue is that when I calculate the same with synonyms using the code below: ...
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1answer
25 views

Decision boundary equation of the perceptron

As I know the standard linear equation has the following form in $R^2$: $w_1 x_1 + w_2 x_2 = b$ where $b$ is the intercept with $x_2$ Also I know that a decision boundary in $R^2$ for a perceptron ...
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7 views

How to validate classifier (built by using MLN method)?

I have developed a method (let's call it Method X) that has a classifier function. The classifier function was built by using MLN (Markov logic network). I need to ...
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3answers
69 views

Does using a kernel function make the data linearly separable?

I'm reading about SVM and I learned that we use a kernel function so the data become linearly separable in the high dimensional (vector?) space. But then I also learned that they use the soft-margin ...
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12 views

Multi-class semi-supervised classification code (SVM, co-training, Graph-based)?

I am trying to evaluate the performance of my semi-supervised algorithm, by comparing it against different algorithms. I have searched a lot, but can't find code that does multi-class semi-supervised ...
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21 views

Feature scaling for classification and regression

Is it true that one should generally scale each of the features before feeding them into common classification models such as Support Vector Machine, Logistic Regression, etc? What about for ...
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1answer
53 views

I want to learn about ROC curve — what is the canonical textbook?

I want to learn about Receiver-Operator-Characteristic curves, and metrics. I have read through online webpages with some basics, and I have used MATLAB built-ins to create ROC plots. It tells me ...
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1answer
41 views

Gradient decay in neural networks

I read that in traditional feed-forward neural nets the gradients in the early layers decay very quickly and that this is 'a bad thing'. But I don't understand why. Can someone please explain what ...
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2answers
27 views

Latent Dirichlet Allocation as input for WEKA

I am using the Weka API for my research about document classification. I wish to apply Latent Dirichelet Allocation on my dataset followed by using a classifier in Weka. However, it is not so clear to ...
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1answer
20 views

Using selected features from a wrapper algorithm to train another model

I was wondering if it can be useful to use selected features from a wrapper algorithm (for example SVM-RFE) to train another classification model like k-NN or Linear regression.
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32 views

Rough estimates for training time of deep belief networks

I'm still learning about deep learning. However I'm currently interested to know if deep learning architectures scale well or not. Suppose I have a dataset with 1 million training examples, can you ...
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0answers
10 views

Why feature maps are indexed by two indices?

I'm reading about convolutional neural networks. As I understood a feature map is a set of neurons (i.e like a single hidden layer in traditional ANN). So why feature maps are indexed by (i,j)? ...
8
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3answers
239 views

Why is logistic regression a linear classifier?

Since we are using the logistic function to transform a linear combination of the input into a non-linear output, how can logistic regression be considered a linear classifier? Linear regression is ...
1
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1answer
21 views

Bayes Decision Boundary and classifier

Is it correct to say that the purpose of classifier (e.g. K-NN, Logistic Regression, LDA) is to approximate the Bayes Decision boundary?
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1answer
40 views

How do we predict rare events?

I am working on developing an insurance risk predictive model. These models are of "rare events" like airline no-show prediction, hardware fault detection, etc. As I prepared my data set, I tried to ...
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21 views

How to compare the results of two classifiers are statistically significant different?

I am applying kNN and SVM classifiers to my classification problem. Both of the classifiers get over 95% cross-validation accuracy (leave one out cross validation used). Not sure how to tell if the ...
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2answers
26 views

What is the minimum training set size required for a given number of features for document classification?

For document classification problems, is there a rule of thumb for the number of training instances required for the number of terms in the vocabulary? I am using a logistic regression classifier ...
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2answers
25 views

Collecting training data for document classification with unbalanced classes

I have a document classification problem in which the estimated class proportions in the population are severely unbalanced: the population is ~99% class 0 and ~1% class 1. I am using a logistic ...
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27 views

how to compute odds ratio

Given a generic classification model $y=f(x_1,x_2,..,x_p)$ where $y\in \left\lbrace 0,1 \right\rbrace$ is it possible to compute the odds ratio for each variable? A theoretical explanation and ...
1
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1answer
54 views

How to define the maximum k of the kNN classifier?

I am trying to use kNN classifier to perform some supervised learning. In order to find the best number of 'k' of kNN, I used cross validation. For example, the following codes load some Matlab ...
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29 views

Finding best parameters of SVM in matlab

I’m designing a system (using Matlab) that I can optimize parameters of a support vector machine (SVM) with genetic algorithm, harmony search and another optimization algorithms to find the best ...
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0answers
28 views

Outlier detection in binary classification

I have a question about outlier detection in my system. I’m designing a system (in Matlab) that optimize both features and parameters of a classification method (like mlp) together with optimization ...
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0answers
5 views

Precision of an incomplete classifier

Given a testing set of nodes which can be either +,-, or 0, I use an incomplete classifier which allows me to predict if a node is +, -, 0, not +, not -, or not 0, and sometimes it cannot predict ...
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35 views

A new piece of clue for document classification?

I am working on a document classification problem. I am using the typical vector space model to represent a document as doc-term vector. If document has some term, the vector entry for that term is ...
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0answers
10 views

SVD Down to One Dimension - K=1

I ran an analysis on a very sparse 40K x 40K customer-item rating matrix for recommendations; I first ran SVD on this matrix using many different reduced rank sizes, k=20,30,40... I used the results ...
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12 views

Complex event processing

I work in an M2M engineering startup and the engineering team have been conceptualizing a complex event processor and want to build "alerts" when an event might occur. The initial plan was to build a ...
1
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1answer
34 views

How to implement a hold-out validation in R

Let's say I'm using the Sonar data and I'd like to make a hold-out validation in R. I partitioned the data using the createFolds ...
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0answers
23 views

Fisher's Exact Test to assess the significance of a difference between false positive rates

I have trained two binary classification models on the same data and evaluated them using the same test set. For each model I have calculated a false positive rate (and a count of false positives) at ...
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1answer
23 views

Should I specify Prior or Cost matrix with Tree Bagger in Matlab

I'm trying to create Random Forests in Matlab and there are more observations in some classes than there are in others. Do I need to specify this as a cost matrix or as a prior probability or will ...
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1answer
24 views

Equal-size categories vs unequal-size categories

I'm trying to reduce the size of my dataset, which is composed of 200,000 projects. Each project is defined by its size and a binary value that is 1 if the project has active users, 0 otherwise. Most ...
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1answer
22 views

ML for specific classification problem

I have a training dataset for classification problem $X \rightarrow y$. Where $X$ is an $n$th dimensional real vector, $y$ is an integer number in $\{0, 1\}$. I want to solve the next problem: ...
1
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1answer
34 views

Why features compression is good?

I'm reading about deep learning and that in principles it's a features compression technique and that is why it works. Now my question is why compressing features from 200 or so into 4 is better? How ...