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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“Non-naive” bayesian classification algorithms

Based on the problem description in this post: Relating parameters to a measured variable Based on a suggestion, I thought of studying the relationship between the parameters and a measured metric ...
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16 views

Classifier that learns provided by only positive examples?

I was wondering if any of you has ever worked with classification/regression using only positive examples (one class). I would need such a system. The basic idea is that it is going to accurately ...
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2answers
21 views

Online learning that “forgets” older aspects learned? (short-term memory)

I am looking for an online learning classifier that is highly adaptable and has only short-term memory. I need such a think in a object tracking system with high-dimensional feature vectors. Maybe a ...
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10 views

Which data transformation can improve the performance of MLP neural networks for classification?

I am trying to fit several MLP neural networks models with a single hidden layer using the caret R-package. My main concern now is in the preprocessing step. My train data features (16 in total) are ...
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14 views

Best technology for keywords to features mapping

Source data = free text ("It's fresh and juicy and sweet") Pre-defined "knowledge" = "fresh" -> quality of a fruit "juicy" -> quality of a fruit "sweet" -> quality of a fruit "sweet" -> quality of ...
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21 views

Information gain and mutual information: different or equal?

I'm very confused about the difference between Information gain and mutual information. to make it even more confusing is that I can find both sources defining them as identical and other which ...
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18 views

SVM with non-negative weights

An SVM classifier can be obtained by solving the following, $\arg\min \frac{1}{2}\|W\|_2^2 + C\sum_i \max(0, 1-y_i (W^T\mathbf{x}_i + b))$ where $W$ is the hyperplane (or weights), $b$ is the bias, ...
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8 views

Advantages of using multiple lstm s in deep network

What are the advantages, why would one use multiple lstm s, stacked one side-by-side, in a deep-network? I am using a lstm to represent a sequence of inputs as a single input. So once I have that ...
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1answer
36 views

Is ROC or PR curve only the overall performance measure for classification

We can use ROC or PR curve to access the performance of the classifier,especially on imbalance data. But it is a curve with parameter threshold, even if we get a high ROC or PR performance, which ...
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11 views

How to use KL-divergence in naive bayes classifier to weight features?

I have a dataset consisting of 4 classes. I have implemented the Gaussian Naive Classifier (in Matlab). In the training phase I calculate the mean and variance for each feature and each class as well ...
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12 views

How to use Weight vector of SVM and logistic regression for feature importance?

I have trained a SVM and logistic regression classifier on my dataset. Both classifier provide a weight vector which is of the size of the number of features. I can use this weight vector to select ...
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24 views

How to use log probabilities for Gaussian Naive Bayes?

I'm currently implementing a Gaussian Naive Bayes classifier. Of course if I'm doing classification by $$ \text{argmax}_{C_i} P(C_i)P(D|C_i), $$ then the probabilities can get very small. So I want ...
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27 views

Adjust p-values for multiple comparisons

I want to evaluate if a proposed modification M* to a base classifier M is better in terms of accuracy. Both, the base classifiers M and their respective modifications M* are tested on N datasets. To ...
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14 views

How can I get feature importance for Gaussian Naive Bayes classifier?

I have a dataset consisting of 4 classes and around 200 features. I have implemented a Gaussian Naive Bayes classifier. I want now calculate the important of each feature for each pair of classes ...
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1answer
41 views

Why is LDA considered to be a classifier?

I am new to machine learning and I was reading about dimensional reduction algorithms like LDA(linear discriminant analysis) and PCA. Currently I am using LDA to find the optimal dimensions that ...
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14 views

Gaze estimation, choosing algorithm and parameters

I am trying to build a program for estimating point of gaze on the computer screen from the x and y coordinates of the pupil centres from webcam video .(x and y coordinates correspond to pixel ...
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31 views

Fisher LDA is a Bayes Classifier?

I've been going over many material in classification algorithms, and it seems that under the constraint that the covariance matrices are the same for a two-class problem then classifying a vector $x$ ...
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1answer
25 views

Proportional odds logistic regression with nominal (unordered) categories

Suppose that you've got a logistic regression with multiple nominal outcomes that cannot be ordered in a theoretically meaningful way. Assume further, however, that the proportional odds assumption ...
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1answer
34 views

“One sided” classifier

Below was tried in R, but any general solution would be highly appreciated: I have 2 class samples (both classes are balanced). I want to create a classifier, where I only care about 1 class (So, if ...
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89 views
+100

Which unsupervised classification method to use next if hierarchical clustering gave bad results?

Purposes I need to perform a classification of weather stations taking into account the characteristics of intra-annual variability of some two climate indicators. There are 613 sites with monthly ...
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1answer
15 views

Training lstm a sequence one item at a time

I am trying to train an lstm with a sequence and get the sequence classification for the whole sequence. I have sequences of varying length so I have one input neuron and I am feeding one item at a ...
2
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1answer
14 views

Comparing performance of a single classifier on two datasets

I'm using a single classifier on two different datasets, consisting of non-overlapping set of observations. The performance on one dataset is higher than the other, and I want to show that the ...
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2answers
76 views

What measure of training error to report for Random Forests?

I'm currently fitting random forests for a classification problem using the randomForest package in R, and am unsure about how to report training error for these ...
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20 views

Problems with classification in imbalanced datasets

I often read about the problematic of doing classification in imbalanced datasets and methods to address it. Namely, off-the-shelf classifiers learn to minimize some form of total miss-clasffication ...
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1answer
31 views

Feature selection in a “Noisy” environment

My first question - This might be a basic question but I have yet to find an answer; when choosing the features for my model, I have encountered certain features which are vectors themselves. (e.g. ...
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41 views

How to quantify performance of Linear Discriminant Analysis (LDA)?

I have implemented Linear Discriminant Analysis (LDA) for dimensionality reduction in C. But I don't know how to quantify performance of the LDA. Could someone help me?
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1answer
31 views

Binary Classification vs Multi-class Classification

In the scenario that I have a binary classification problem, and use a binary classifier to train and test my model, assuming everything else is constant, would using a multi-class classifier with 2 ...
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31 views

Personal bet suggestor

Hi which regression or classification algorithm gives the best suggestions for future bets. i have a small training data base (approximately 50 data) consists my old BET coupons and old results. And ...
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34 views

SVM classification [closed]

Please ,I need to know how start image classification by svm in matlab ? Like this image
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8 views

How does the value of random state affect the prediction accuracy in sklearn?

I was doing a split on my train and test data for the iris dataset and trying to randomize it. I have the following code. ...
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1answer
10 views

classifications for many multiple classes (40)

I need to classify records in 40 different categories. What would be the best approach to it? Logistic regression? I though it is used for revealed preference and I don't have the other possibilities ...
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131 views

Huge Discrepancy between OOB and Cross Validation Random Forest

I am dealing with Random Forests at the moment. I observe huge discrepancies between OOB generalisation error estimation and cross validation. Originally, I used the scikit-learn package. But to ...
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1answer
30 views

how to minimize the probability of error in a Bayes decision rule

According to the Bayes decision rule for a 2 class classification problem: $d(x) = w_1 : P(w_1 |x) ≥ P(w_2|x) $ And $P(error|x) = min[P(w_1 |x), P(w_2|x)]$ where $P(w_i |x) = p(x|w_i) * P(w_i)$ ...
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1answer
30 views

Classification trees: favor one classification over other

We're using classification trees (c50 package) for a BUY/WAIT advice. However, the advice in our training set is not well balanced. That is, we advice to buy 3/4 times more than to wait. Probably as ...
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44 views

why use diagonal $\Sigma$ when working with Bayes decision theory?

My prof. said in the class that for Bayes decision rule, the likelihood is Gaussian and in practice, we will almost always work with a diagonal $\Sigma$. Why is that? I know that a diagonal $\Sigma$ ...
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1answer
32 views

pattern classification when the prior probabilities are not equal

In the case of 2 class classification, the decision boundary occurs when 2 discriminant functions are equal: $$ g_1(x) = g_2(x) $$ $$ g_i(x) = p(x|w_i)P(w_i) $$ $$ p(x|w_i) = ...
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1answer
34 views

classification tree with R part

I am trying to grow a classification tree with a few continuous explanatory variables and a few factor variable. It seems the Rpart alogrithm is ignoring the factor variables. The differences are ...
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1answer
54 views

Relating parameters to a measured variable

I have an ordinary differential equation based model for a system which depends on 16 parameters (all continuous and positive). I have 10000 random sets of parameters where each set has 12 elements. ...
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10 views

Comparing two empirical distributions using mean and variance

I want to compare two classifiers (random variables). Each classifier is binary variable. I have evaluated the two classifiers on different set {S_1,S_2,..S_m} each with N samples, and calculated the ...
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14 views

validation set with ranking variables

i'm working on an approach of feature selection with SVM model and i have some questions about validation , training and test sets. the idea is to rank variables in decreasing order of relevance ...
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2answers
39 views

Multi-label classification

I am working on a project and I need some suggestions. I have a data set with 600 songs and for each song we have 60 numerical features (linked to the rhythm and the timbre of the sound). Moreover ...
3
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2answers
103 views

Finding incremental users using A/B testing

Let's say you run an A/B test with a new webpage, and a control (the old webpage). Your new webpage has an 11% response rate, and your old one has 10% response rate. Let's assume population in these ...
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1answer
35 views

How to predict new data with a classification tree in R?

I have built a classification tree for factor variables with the rpart package and now I want to predict unseen data with it. How can I get a sense of whether the model is good at predicting unseen ...
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28 views

Which classification techniques perform efficiently under homomorphic encryption

I am reading a paper (pdf) on homomorphic encryption and its use in machine learning. This paper explores classification methods like Fisher Linear Discriminant Classifier (FLD) and the Linear Means ...
0
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1answer
30 views

How to deal with linear regression intercepts with high p-values in dichotomic classifier?

I have used a simple multivariable logistic regression (as you would get by default glm() with logit in R) in a problem of dichotomic classifier with approx. 100 predictors, i.e. quite a lot of ...
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19 views

Equivalent measure to Matthews correlation coefficient, MCC, for multiclass classification

Thanks in advance for the help. MCC gives a measure of the quality of a binary classifier. I'm looking for a similar measure that can be used for a multi-class classifier. Ultimately what I would ...
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2answers
36 views

How much each variable contribute to my overall classification

Les say I have a data set with several measures and one factor (classification) like the one bellow (for the sake of simplicity, I'm simulating 10 rows and 5 variables only) I'd like to know how much ...
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1answer
18 views

How to detect classifier curve in non-separable SVM problem

Suppose we want to classify two class of data that are non-separable with hyper-plane. So we use kernels to map data to high-dimensional space. See my codes: ...
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67 views

Train a Neural Network to distinguish between even and odd numbers

Question: is it possible to train a NN to distinguish between odd and even numbers only using as input the numbers themselves? I have the following dataset: ...
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16 views

How to optimize RBF parameters $C,\gamma$ with KSVM method?

I want to find the best choice of $C$ and $\gamma$ parameters for Radial Basis Function kernel. I am using kernlab instead of e1071 library. So how can i optimize RBF parameters $C$ and $\gamma$ with ...