Data organized into discrete categories or *classes* may present problems for certain analyses if the number of observations ($n$) belonging to each class is not constant across classes. Classes with unequal $n$ are *unbalanced*.

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422 views

Softmax regression bias and prior probabilities for unequal classes

I'm using Softmax regression for a multi-class classification problem. I don't have equal prior probabilities for each of the classes. I know from Logistic Regression (softmax regression with 2 ...
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697 views

Mixed-effects model for a strongly unbalanced design

I am somehow unsure on the best option to analyze these data. Here is my study case: The response variable is a morphometric measure, one for each individual. During 10 years, say 2000-2009, people ...
3
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79 views

multiclass unbalanced data

I am trying to predict crimes (san francisco) using machine learning algorithms. Its a multi class classification problem with unbalanced data. I took sample of data ranging from years 2010 to 2015 ...
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68 views

Precision in unbalanced multi-class problem

I am dealing with a multi-class classification problem and I compute micro-averaged evaluation metrics (precision, recall and F-measure) by performing 10-fold cross validation. However, the fact that ...
3
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0answers
264 views

Mixed ANOVA: small and unbalanced samples

I have to analyze two samples ($n_1=10, n_2=18$) in a design in which there is a between-subject factor (Groups: 2 levels) and a within-subjects factor (...
3
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0answers
648 views

Problem with classifier after using SMOTE to balance the data

We've ran into a problem while training a classifier on an unbalanced data set. The response is binary with 0 indicating 'non defaulter' and 1 indicating 'defaulter' (it's a credit scoring task). ...
3
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552 views

How to use k nearest neighbours for binary classification with unbalanced classes?

I have relatively large (100k items) dataset which I need to split in two groups. So far I've tried knn and the results are not good mainly because I have disproportion in my training data: 90% of ...
2
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0answers
19 views

How to set sum contrasts for unbalanced factors

Let's say that I have a model where the response time depends on accuracy (0/1, coded either as categorical or numerical) and another categorical variable (pres: idem/diff), both interacting with the ...
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16 views

Interplay of Training Class Sizes, Class Weights, Loss function and Decision Threshold

I am facing a two-class classification problem where: There is way more training data in class 1 than in class 0. Classifying a class 0 event as class 1 has a higher loss than classifying a class 1 ...
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35 views

mixed effects modelling of unbalanced repeated measures data

I have radio tracking data on 34 animals over a period of up to 26 months. For about 6 animals I have all the data, for 2 others I only have a couple of months, and the rest lie somewhere in between. ...
2
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164 views

Is using Rpart with unbalanced data a good idea?

I have a rather unbalanced data set and want to use rpart to build a classification tree. After building the full tree, I prune it back using the 1-SE rule. On average, only 1-2 splits are suggested. ...
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50 views

Unbalanced groups and classification errors

I would like to adopt a general strategy for dealing with an very unbalanced dataset, where my "positive" group corresponds to 1/40 of all the observations. The reason why I ask it is because all the ...
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486 views

Average of predicted values with logistic regression

I have a large unbalanced dataset (the target has ~1500x more 0's than 1's) on which I train a logistic regression algorithm to predict the probability of success (Not a binary outcome but a real ...
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268 views

Unbalanced panel data: Fixed effects?

I have an unbalanced panel dataset with N=10 firms and T=61 days. Because one variable had values outside the theoretical range I had to constrain my dataset, which left me with only 239 observations. ...
2
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0answers
515 views

Repeated measures ANOVA for an experiment with missing values

I have an experiment where several subjects (subjects $= S_1,S_2,...,S_m $) were asked to perform a set of tasks (tasks $= T_1, T_2, T_3,...,T_n$) using both their left ($L$) and right ($R$) arms. ...
2
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685 views

How to analyze an unbalanced within-subject ANOVA design?

I have data from an experiment involving 4 groups of subjects, 2 possible interventions first and 3 possible intervention at a 2nd point, repeated data measurements from each subjects multiple time ...
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13 views

How to retrain a production classifier that blocks its own positive examples?

I'm looking for help understanding how to re-train a fraud detection classifier that's been deployed to production (where it successfully blocked much, but not all fraud coming into the system). I ...
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23 views

Tuning priors/weights/costs to counteract class imbalance

I have a classification problem which consists of two classes. It has high class imbalance. There are around 85% data points for the negative class and only 15% for the positive class. One option is ...
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37 views

Unbalanced two-factor repeated measures ANOVA with missing values

For my data set, I need to perform some sort of two factor repeated measures ANOVA. I have one between-subject factor called "Treatment" and one within-subject factor called "Frequency" with 8 levels. ...
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30 views

How to handle with “in class” imbalance in machine learning?

A lot is written about class imbalance in machine learning (for example on this site here). However, how to deal with "intra class" imbalance? Assume I want to classify Bikes v.s. Cars. My training/...
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71 views

Solve unbalanced data set problem in binary classification time series prediction (sampling methods)

I'm using time series data (continuous features) for binary time series prediction (one step ahead, up-turn and down-tern of output of t+1 comparing to ...
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69 views

What post hoc test should I run for a significant interaction in a two-way unbalanced ANOVA?

I have data with two factors (Category and Treatment) and each factor has two levels (A and <...
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0answers
22 views

Chi-squared test of independence for biased data

I'm working with a survey dataset consisting of 28807 observations (8470 males and 20337 females). I'm trying to determine the association between dichotomous variables, for instance, sex (Male, ...
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42 views

Class imbalance problem and baseline classifier

I have a dataset with four numerical attributes and a class (target) variable. There is an enormous imbalance between positive and negative instances according to class variable. To cope with ...
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76 views

For classification w unbalanced datasets, is class-weighing the same as oversampling?

in unbalanced classification problems, I find myself using class_weigh = "auto" or similar parameters often, but I don't think I'm fully understanding what it's doing. I know that it's the industry ...
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26 views

Should the number of normal samples always be more than that of anomalous samples in training set for anomaly detection?

I am trying to train an anomaly detection algorithm (one-class svm) on a data set with a few hundred positive samples and several thousands negative examples. Is it mandatory that I train the model ...
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139 views

Non-parametric Levene's test by Nordstokke and Zumbo

The example they mention is using a one-way ANOVA. What if I have two factors (3x11) and a dependent variable, can I do a two-way ANOVA to calculate the univariate levene's test? If so, how would I ...
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79 views

positive and negative sample count for ConvNets

I have been trying to set up a ConvNet to classify some data. This data should be classified to either 1 (being what I need to get from the image) and 0 for everything that is irrelevant. I have ...
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24 views

Multiclass target detection : N X (1 vs all) or 1 X (N vs all) ?

I am doing a multiclass classification using neural networks. say I have 10 target classes and one null (non-of-the-above-targets). is it better that I train a neural network separately for each ...
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0answers
64 views

Achieving high recall for smaller class in unbalanced linear svm

I have an svm-related question. I have an unbalanced dataset, meaning classA could be 1/10 to 1/35 of classB. Well I am interested in getting a linear svm which would separate the data and would ...
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194 views

How to do a power analysis for an unbalanced mixed effects ANOVA?

I need suggestions for how to calculate the $n$ required for 80% and 90% power for >30% change from baseline ($T_0$) at $T_1$ or $T_2$, drug vs. placebo, 2:1 ratio; 20% CV in test; factors: subject, ...
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48 views

Is it correct to compare two distributions of observed (that are means of observation) and expected values with chi square?

I have 2 classification methods that I want to compare. So I ran them on the same dataset and I obtained 2 different classifications. Then, I want to test if their classification is robust and how. ...
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104 views

Testing classifier with binomial test when group sizes are unequal

I have data from 50 human subjects, who are divided into groups A and B (30 participants are in group A and 20 participants in group B). I also have a range of measurements from each subject. I have ...
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361 views

Questionnaire analysis and grouping responses

I want to know if the creative process engagement (CPE) is related to creativity. I don't know how to analyze the questionnaire. I will be collecting data for CPE with Zhang and Bartal's (2010) 11-...
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0answers
93 views

Type I ANOVA tests not depending on the order of the factors

I have a dataset with two factors A and B and the following design (contigency table showing the number of individuals for each ...
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0answers
125 views

Different Mean Square partitions in an unbalanced bifactorial ANOVA (with random factor) between R and Statistica

I am trying to extract variance components for selection and chance in a bifactorial design with Generation as a fixed factor and Replicate as a random term, for early fecundity. Since I am using ...
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232 views

How to compare multiple groups of unblanced repeated measures non normal data?

I'm trying to compare three groups data. But the data set is about a new drug trial. The data set has these characteristics: Follow-up set. That is, after administration of the drug, a series of ...
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5 views

Where to start on understanding Adaboost for an unbalanced multi-class problem

I need a better classifier for an unbalanced multi-class problem. I'm tempted to implement Adaboost as an exercise in understanding it since it is quite clear and simple, but am unsure how to deal ...
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0answers
6 views

Setting effect weights to sum-to-zero in linear mixed effects model with unbalanced data

I am fitting a linear mixed effects model to longitudinal data. There is a between-Subjects factor Group with three levels (Info,...
0
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0answers
14 views

Learning from Multiple Naive Annotator's Presence (and their labels as Y)

Although I am new to the forum, I have been following for several years and wanted to begin by sincerely thanking everyone, from the administrators to the members, for creating such an amazing ...
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44 views

Recursive feature elimination and class imbalance

I am trying to apply the recursive feature elimination in the R package caret following the example in the caret website: ...
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0answers
16 views

What is the effect of class weight in Random Forest/Extra Trees Classifier variables importance?

In the sklearn implementation of random forest and extra trees classifier a class_weights parameter is available http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier....
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21 views

How to analyze differences between two time series collected under two different conditions

How should one analyze time series data that were collected during two seasons: season 1 and then at season 2, where during each season a measurement sample for several continuous variables were ...
0
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0answers
22 views

Learning with unbalanced classes

I have a biometric data set of size $n \sim 150,000$, with $p=21$ features $x_1,\dots,x_p$ representing information about people $-$ some categorical and some numerical. The original data set had only ...
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0answers
13 views

Literature (guidelines) on unbalancedness in two-way within-subject ANOVA

I am looking for literature (guidelines) which discuss the consequences of unbalanced designs on running a (two-way) within-subject ANOVA and pros/cons of various counter-measures. I came up with ...
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0answers
7 views

Rebalancing doesn't give good results

We have a given a group of customers a price increase and as a result some have cancelled. We can identify exactly who they are because of the way they cancel. This means I can split them out from ...
0
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0answers
20 views

Unbalanced Repeated Measures Anova

First Question: I would like to double check that my code is doing what I think it is doing. I have two independent variables, Previous drilling and Soil Type, that are observational. Simpsons ...
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0answers
21 views

What to do with highly unequal sample sizes in a dummy linear regression? (+ nonnormal distribution)

I am conducting a multiple linear regression analysis in SPSS. My DV is continuous (score between 0 and 6), and my predictors are: one dichotomous nominal variable (native vs. non-native speakers) ...
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0answers
26 views

How to add hard negatives to original training data?

I have 2 class binary classification problem with original training data of size N=n_pos+n_neg in general case n_pos!=n_neg but now we can assume that number of positive and negative examples near the ...
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0answers
56 views

Caret classification: feature selection & unbalanced data

I have a two-class classification problem with very unbalanced data (~1:1000 Yes/No ratio). The initial model class I'd like to try is regular glm. So there are two issues need to be addressed: 1) ...