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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9 views

Decision Trees with Overlapping Response Variables

Background information: Response: If the respondent owns a car (Toyota, Honda, BMW,etc.). There are multiple response columns as people can own multiple cars. So for example, the first respondent ...
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13 views

Training instances importance in Random Forest?

Is it possible to determine the importance of the training examples in Random Forests, analogously to what's done with predictors? Basically the idea would be to find important samples in the data, ...
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1answer
13 views

How does data augmentation reduce overfitting?

I'm trying to understant the benefit apported by the step of data augmentation in a classification algorithm. I have a vector of hexadecimal strings and a column vector containing the label ...
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1answer
9 views

difference in meaning between Soft Clustering and Multi-classification techniques

Dear Weka subscribers i would like to know the difference in meaning, approach and concept between : Cluster similar objects into more than one cluster ( soft clustering ) where objects can be ...
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1answer
29 views

What method for classification with 24 variables, 14 categories and 100,000 obs.?

I have a dataset with more than 100,000 observations (rows) and 24 variables in which 23 are continuous and one is categorical variable. The categorical variable has 13 categories (1, 2, 3, ..., 13) ...
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10 views

How to define an appropriate timeframe to report model performance metrics

I have built a credit fraud identification system that classifies clients as either fraudulent or not fraudulent. To evaluate this model, I am using metrics such as accuracy, recall and precision. ...
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0answers
12 views

likelihood ratio test [on hold]

I need to use likelihood ratio test (LRT) for a tow hypotheses classification problem. H0 denote background class and H1 for target class. where it is assumed that this to class have Gaussian ...
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0answers
21 views

The covariance matrix is not positive definite in a classification task in Matlab

I am trying to perform a simple classification task in Matlab. I have an NxM matrix F with rows representing the samples and column representing the features (that is my training set). This is fed to ...
-1
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0answers
18 views

Global Minima and Local Maxima in Random Forest Classifiers in R [on hold]

I am learning Random Forest Classifiers and I want to know how can we determine the Global Minina, Local Minima, Local Maxima of a Random Forest classifier. Can some one help with this?
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14 views

Combining a classifier with average travel times

I'm working on the following problem: I'm trying to predict if a subway is moving or stationary based on the accelerometer profile that I collected with a phone. I used the acceleration data to train ...
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0answers
10 views

How to use unsupervised classification to “test” labels of supervised classification

If i know $k$ labels i can do a supervised classification. Have any sense perform also unsupervised classification and made a prediction table to understand if the new $k$ label of unsupervised are ...
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2answers
28 views

How to apply classifiers from k-folding to data not used in the k-folding?

When I am using k-folding to split my labelled data (labelled as signal or background) and train k classifiers on it, I believe I am not allowed to assume that the distributions of the classifier ...
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0answers
7 views

Kappa for classifier evaluation with ground truth data

for a fraud detection (credit-scoring-like) problem I want to use kappa as an evaluation metric. Kappa has the nice property that it fits very well to a problem with highly imbalanced relation between ...
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0answers
24 views

How to deal with categorical target variable that has more categories in prediction than training?

I'm building a logistic regression model and found out that with my categorial target variable there are more categories in my prediction set than my training set. To be clearer: In e.g. my training ...
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0answers
28 views

Method to predict action based on previous sequence of actions

Given $n-1$ sequences of actions [$k_{i1}$...$k_{in}$] as training/example I want to be able to predict $k_{nn}$ in the sequence [$k_{n1}$...$k_{n(n-1)}$] where $k_{nn}$ would be the most likely ...
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1answer
15 views

Twitter Classification of tweets related to Ebola into 21 custom categories

I have a lot of twitter data (4GB) related to keyword Ebola. I want to classify the tweets into 21 categories. Categories :- Death - tweet is about death Health Care Workers - tweet is about ...
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0answers
4 views

Mahalanobis vs Bhattacharayya distance

I am currently trying to study class separability in a binary classification problem. I found Bhattacharayya distance to be a good (and canonical) separability measure, but it appears that Mahalanobis ...
1
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0answers
23 views

Classification trees - how to avoid “cherry picking”?

This post How to compare the performance of two classification methods? (logistic regression and classification trees) represents a very similar problem I am just trying to solve - I have a dataset ...
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1answer
18 views

Classification method with (potentially) endless training input

What is the best multi class classification method with (potentially) endless training input? The classificator should get trained while a user interacts with the system. At this time it gets ~ 30 ...
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0answers
13 views

time series classification of an event either happening or not happening using machine learning techniques

I have sensor data that I would like to use to classify whether an an event (giving birth) is about to occur within (2-4hrs) in an animal based on various metrics collected by the sensor(activity ...
2
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2answers
23 views

Incorporating features that are always 0 given the value of another feature into a decision tree?

If I'm building a decision tree model, what is the best way to incorporate features that are always 0 given the value of another feature? For example, imagine I'm predicting whether or not someone ...
0
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0answers
16 views

Sample size needed for prediction modeling/validation with logistic regression

I have a dataset with about 30 potential predictors and 115 observations. I'm looking into building a prediction model with the data using logistic regression. From what I have read - the typical ...
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0answers
7 views

Objects and properties classification

I have a list of properties and objects: ...
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1answer
17 views

Reduce false positives with XGBoost

I'm dealing with a dataset that contains almost same number of positive and negative samples (there are around 55% of positive samples and 45% of negative samples). With XGBoost I'm managing to ...
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0answers
7 views

Why is xgboost giving bad scores and taking a very long time? [migrated]

I am completely new to xgboost so thank you very much for any help in advance. I have this simple script. ...
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0answers
12 views

How to approach this classification problem? [closed]

I have spaces with multiple rectangles on them. for each rectangle, I have the coordinates of its 4 points (x1, y1), (x2, y2), (x3, y3), (x4, y4) relative to the ...
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0answers
7 views

Suggestions on choosing correct method for multi-class classification of imbalanced data

I have data that is split into three classes (A, B and noise). The data amount is around 10000 samples, and A and B is only less than 5-10% of data. What is the best approach to handle this situation ...
2
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2answers
50 views

AUROC equal to 1.0 means overfitting?

Evaluating the classifier I implemented for university, I am observing an AUROC (Area under curve of the ROC) of 1.0 (which means a TP rate of 1 and a FP rate of 0.0) The dataset used for training ...
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0answers
24 views

Weka Decision Tree not working on real data

I'm trying to make human activity recognition using the iOS accelerometer and gyroscope. The feature that I use are mean, variance, standard deviation, energy and cross-domain entropy. If I provide ...
-1
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0answers
15 views

LIBSVM data format [closed]

New to LIBSVM, can someone tell me how I can format for example the ala datasets from the UCI collection in order to classify the data in Matlab.
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0answers
17 views

Classification with Gaussian Mixture Models

Say I have two classes A and B where I have to use GMM to do classification. I wish to come up with a metric that captures how well the choice of model order for each class does against prediction. ...
3
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0answers
40 views

R package for classification and outlier detection together

I have a similar problem as this one. My training samples contain N observations and K>2 classes. I want to classify my test samples into one of the K classes, or as an outlier if it is far from any ...
1
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1answer
18 views

Gaussian Processes Probabilistic Least Squares Classifier - Leave one Out Cross-Validation Means, Variances Shape?

I am currently working on implementing some of the algorithms covered in Rasmussen and Williams' book, and stuck on a particular part in chapter 5 (link to the chapter here). In particular, on page ...
0
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1answer
23 views

How to embed prior distribution of datasets into the classification model

Given 3 training sets : $(X_1,y_1),(X_2,y_2)$ and $(X_3,y_3)$. These three datasets are separated as it is being manually tagged in the preprocessing. Based on the datasets, three classifiers can be ...
1
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0answers
15 views

Determinant of confusion matrix: how useful is it as a performance metric?

I was thinking a bit about confusion matrices and it came to my mind the determinant of a confusion matrix could be an useful performance metric in classification. Indeed, I got some results in ...
2
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0answers
19 views

How are performance measures affected in PU learning?

When learning from only positive and unlabelled data (PU learning), how are performance measures affected, when compared to a standard supervised setting? For simplicity, let's assume that the entire ...
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0answers
20 views

population data normalization

I'm running a prediction model on demographic data, to predict a given feature (e.g. salary range) given age, zip code, gender, job title, ... I have a data set of 50K persons and I reach an accuracy ...
3
votes
1answer
31 views

Predict probability when model was trained in balanced dataset

I have a dataset of about 1M observation and I had to predict a response that occurs only about 10.000 times (1%). I decided to train a random forest, but this takes a lot of time to train because ...
0
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0answers
16 views

Evaluate subsection of confusion matrix

I have a series of models with multinomial responses and I am evaluating them with a confusion matrix like this. A B C A 9 2 1 B 1 8 6 C 0 7 7 Now, my ...
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0answers
13 views

Prediction of multiple time series with classification

I have multiple time series of air passenger demand with specific classification data. Data looks like this (some rows may lack some data): ...
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0answers
14 views

Postage Stamps recognition what to use

I have some stamps collection maybe 4000-5000. I dont know anything about them. But it's exists a lot of albums. The main proble is how automatically recognize and find a match. I think that the ...
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0answers
12 views
0
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0answers
10 views

Improving decision tree plot quality using rpart module

I am working on implementing decision trees to classify a target variable using R .I have around 21 features with around 800,000 rows.I am using rpart package to plot the tree I get,I have tried a lot ...
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0answers
12 views

can anyone help me to find out the working of Expectation Maximisation clustering [closed]

1)how clusters are build using EM clustering when given a set of data points as input. 2)how EM is different from k-means clustering. 3)give a detailed explanation of E-step and M-step of EM ...
0
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0answers
8 views

Can class probability be obtained from regression results?

I am using regression to solve a classification problem. The basic idea is to put the regression results into several intervals defined by the classes. When I solve pure classification problems, I ...
0
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0answers
18 views

Doing cross-validation when diagnosing a classifier through learning curves

I have a theoretical question on the correct way to make learning curves to diagnose a classifier. To see a generic example of these curves one can refer to this (min 34 onward) lecture by Andrew Ng ...
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0answers
18 views

Term for k-nearest neighbors of same class

Is there a term for saying that all neighbors are the same class?
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0answers
14 views

How to use same metric in rfe and train?

I'm running a feature selection together with a model tuning using caret's rfe and train methods on a multi-class problem. I would like to select my features in rfe, as well tune my model parameters ...
0
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0answers
11 views

Supervised Binary classification with numerical and text data

I have dataset in which some features take numerical values and some features take only arbitrary text(note that it is not categorical in nature). Each row has a target of 0 or 1. How would I apply ...