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

The best way to solve particular classification problem?

I got training set (time series) of size approximately 2 million precedents {x,y}. Each x is a vector of size 20 and each y is a binary vector of size 10 like {1,0,0,1,1,0,1,1,1,0}. For a new input x ...
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22 views

Order of preprocessing steps in a binary classification problem

I have these stages (ordered) for preprocessing in my binary classification problem. Dividing data based on criteria (class1 and class2 databases) Outlier ...
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1answer
20 views

Best algorithms for ordinal classification

I am working on a data set of about 34K rows trying to predict an ordinal response variable using R. I have tried association rules, random forest and ordinal regression. Does anyone have experience ...
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0answers
30 views

Cutoff and precision values of a binary classifier

Let's say I have fitted a binary classifier to some data and I'm varying the cutoff value, effectively producing a ROC-curve. Knowing the true proportions of positives and negatives, I can calculate ...
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1answer
46 views

Classification using correlation

Given two correlation matrix (each $p \times p$), where each belongs to a different group, is it possible to classify a new sample into one of the group (based on the correlation matrix only)? What ...
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1answer
48 views

How to change threshold for classification in R randomForests?

All the Species Distribution Modelling literature suggests that when predicting the presence/absence of a species using a model that outputs probabilities (e.g., RandomForests), choice of the ...
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19 views

different feature types for classification

There has a data set with several features. One feature is of the type of continuous numerical values; another feature is of the type of categorical values, such as A, B and C. If I want to build a ...
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13 views

labelled spam classification dataset (not e-mail) [on hold]

There is an abundance of spam e-mail classification datasets out there, for example: http://archive.ics.uci.edu/ml/datasets/Spambase But after searching Google I cannot find a similar dataset for ...
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7 views

Clustering techniques when there are two distinct but numerically similar clusters among others

I'm trying to cluster some spatial statistics for some behavioral estimation. However, parts of the trajectory report exactly 0 speed, which implies some kind of resting state which is different from ...
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1answer
17 views

R regression with categorical response variable

I have four variables, two are categorical and two are numeric: ...
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2answers
134 views

When to avoid Random Forest?

Random forests are well known to perform fairly well on a variety of tasks and have been referred to as the leatherman of learning methods. Are there any types of problems or specific conditions in ...
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1answer
15 views

Use random forest outliers to detect group of variables

I have a input data and an output binary variable . The y value is 1 if the patient get ill. ...
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14 views

Comparing 2 classifiers with different feature vectors based on same training and test data

Let us assume we have two classifiers C1 and C2 which are based on different feature vectors, ...
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9 views

Completing a matrix whose entries depend on time

Imagine you have a matrix, where each row represents an individual and each column represents a specific time interval. The entries of the matrix represent events occurring for a given person at a ...
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65 views

How many eligible bachelors in a city?

This is a very simple question posed to me by a friend of mine. I know it's a statistical analysis problem, but I suck at math. Given the total population of $x$ within a metropolitan area, what ...
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8 views

automatic assign class name based on text

My question is , I have a set of plain text , i want to create category based on the text. Eg: i have written something about Soup recepie then the algorithm must create a category called Food. After ...
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1answer
58 views

Outlier detection in out-sample data for the purpose of classification

This is the most widely used method for outlier detection in econometrics and statistical problems. X is our data that we're searching for outliers in it (in ...
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29 views

categorical feature ranking

I would like to rank categorical features by the order or importance in a classification/regression setting. Input There are two features, which are survey questions: "how is your mood?": four ...
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1answer
19 views

How should the precision/recall be calculated for classes in datasets with NO true class instances?

I have built a classification model to recognise a class and I have evaluated it on several datasets. The problem is that some of these datasets do not have any true instance of the class in question, ...
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0answers
3 views

what is the meaning of the Samples in NER?

I would like to know in NER (Named Entity Recognition ) problem , which concept should be considered as samples? each token as a sample? or each sentence ? or each Named Entity should be considered ...
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34 views

Selecting individuals from a population using a binary classifier

I have a dataset consisting of around 200 individuals, whose outcome is either of state $0$ or $1$. I am able to make binary classifiers and predictors on this set and build ROC-curves for them just ...
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33 views

Adaptive Boosting vs. SVM

I am working on a binary classification case and comparing the performance of different classifiers.Testing the performance of adaboost algorithm (with decision ...
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0answers
13 views

Implementation of batch Hieron

I would like to implement the Hieron algorithm, which is described in the paper "Large Margin Hierarchical Classification". The basic online Hieron is specified in the paper, but I need the batch ...
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3answers
115 views

ROC graph shape

Could you explain to me how the shape of a ROC curve is determined? From the following illustration, it seems that for every time the actual class (C) is positive, it goes up and when it's negative, ...
2
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0answers
39 views

Unbalanced dataset - ROC curve to compare classifiers?

I use the machine learning software WEKA for data mining on biological data. I would describe my dataset as unbalanced: It comprises around 2000 instances, ...
2
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2answers
86 views

Reproduce linear discriminant analysis projection plot

I'm struggling with projection points in linear discriminant analysis (LDA). Many books on multivariate statistical methods illustrate the idea of the LDA with the figure below. The problem ...
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2answers
36 views

Evaluating predictive models

I am looking for ways of evaluating the performance/success of predictive (classification) models for economic purposes. I know of: Direct accuracy percentage AUC score Net profit Rate of return ...
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0answers
8 views

Inconsistency in labelling a class for a churn prediction problem

I'm modelling a classifier to predict churns. I have a set of training instances which are a tuple of the form (attributes, label) where the label says whether they are active (call the label as "A") ...
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8 views

How can the quality of features be evaluated in high dimensional classification tasks?

I am currently experimenting with on-line symbol recognition for mathematics for my bachelors thesis. I have 369 symbols which I would like to distinguish. There are a lot of preprocessing methods / ...
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19 views

Document classification problem

Assume we have $L$ labelled documents, and $U$ unlabeled ones, where all the documents from class $k$ were generated from a multinomial or Naive Bayes distribution with parameter $\theta_k$, and ...
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25 views

Parameter optimization of SVM

Currently I am using SVM to perform some classification task. I use libSVM with Matlab interface. From the practical guide of SVM (Link), we know that there are two parameters need to be tuned, namely ...
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0answers
9 views

In binary classification, what label imbalance is acceptable to not to care?

I have a pretty large set of binary-labeled data (~20K rows, ~100 columns). Approximately 20% of the data is "positive" and 80% is "negative". In my case every classification error has the same ...
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0answers
9 views

Weka: cross validation using blocks of related instances (leave one patient out)

I have a dataset that comprises several instances for different patients, with multiple instances per patient. I need to perform some classification tasks and I was using cross-validation, but this ...
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0answers
11 views

Learned production test

To validate the acoustic performance of a product, we are using hand-engineered features and thresholds. Everytime a new hardware problem arises we have to at least tweak a parameter and at worst add ...
3
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0answers
35 views

Priors for discriminative methods?

Say we want to build a classifier for a binary classification problem using a discriminative method (e.g. SVM) and be able to impose a prior on the classes. For example, let's assume that we want to ...
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0answers
21 views

semisupervised classification training on all or part of unlabeled data

I have 3 sets of data. A positively labeled dataset. An unlabeled dataset that has for sure positive (around 75%) and negative data. An unlabeled dataset that has for sure positive data and maybe ...
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1answer
41 views

Using the Caret package is it possible to obtain Confusion Matrices for specific threshold values?

I've obtained a logistic regression model (via train) for a binary response, and I've obtained the logistic confusion matrix via ...
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4 views

How to compute the normalized misclassification error and the misclassification error?

How is usually computed the normalized misclassification error ? I would like to know the formula for a 2 class problem of size $s_1, s_2$ and for a k class problem of size $s_1,\dots, s_k$ I would ...
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18 views

How to: cross validation and scaling features using LibSVM – binary classification problem

I have a matrix of samples in rows and features in columns. I want to train this data matrix using LibSVM. How can I normalize or scale my features before running LibSVM? How can I perform cross ...
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0answers
23 views

Conditional Inference trees on correlated observations

I have a dataset containing a binary response variable and a few numeric predictor variables. I would like to use Conditional Inference Trees algorithm in R using the ctree function in party package. ...
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1answer
32 views

How to avoid random forest overfitting and improve prediction?

I have an input dataset x_train and an output dataset y_train ...
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0answers
22 views

logistic regression using probabilities of class labels

My goal is to train a logistic classifier. My samples in my dataset have some label noise but for each label I can give a probability how correct this label is. What is the best way to incorporate ...
0
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0answers
16 views

Extraction of a decision boundary (LDA) after a systematic querying of the feature space and convolution with Sobel filter (examples in numpy)

I am doing some experiments with LDA (Linear Discriminant Analysis), in python. Now I am at the point in which I would like to display the separation planes in the 3-dimensional feature space. I ...
0
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1answer
43 views

Interpreting logistic regression output - model w predictors is no better than constant

I'm running a logistic regression (N = 15000) and the percentage accuracy in classification (sensitivity) of the model with predictors included = 0 (the SAME as the constant model without predictors). ...
0
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1answer
33 views

Random Forest Usage

Random Forest Usage: I have run random forest in R. It gave me confusion matrix and variable importance. Variable importance can be used to rank importance of variables in the model. My question is ...
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2answers
68 views

How can I partition a distribution into two sub-populations with fixed bias? (simulation)

I am trying to simulate a selection model for a variable $Y$ dependent on covariate vector $X$, so that two groups/sub-sets $S=(0,1)$ of observations on $Y$ are created, which have a fixed difference ...
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0answers
27 views

Entire data considered as support vector

I am currently learning to use support vector machine as classification. I have a data set with 161 observation and 18 dimension. I get 160 support vectors using svm function form R package, e1071. ...
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1answer
84 views

calculating probability or filtering that certain subject is not in the particular cluster

I have a situation where there are n individuals and p features (variables). I do have their cluster information. Here is an example: ...
3
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1answer
46 views

ROC-AUC and Precision-Recall for random classifiers in class imbalanced problems

I have always always understood the diagonal of the ROC plot to represent the performance of a "random" classifier (corresponding to an AUC of 0.5). Is this still the case for highly imbalanced ...
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0answers
24 views

Walking recognition

I have walking samples from 20 different people. My aim is to detect which walking samples are from which person. I'm trying to achieve this by extracting "walking cycles" from each person's dataset ...