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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469 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 ...
4
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0answers
333 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 ...
3
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0answers
55 views

Bias Correction for Large Scale Logistic Regression with Rare Events

I have a large dataset constituted of many ad impressions. My dependent binary variable clicked describe whether or not the ad was clicked on. As you can expect, the number of clicks is about 1000x ...
3
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0answers
229 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
410 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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0answers
297 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
34 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 ...
2
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0answers
181 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 ...
2
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0answers
174 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
198 views

Training and testing on Unbalanced Data Set

I used SMOTE algorithm in R for class balancing. My data size has 13000 rows, I had 7% minority class in my sample now I used SMOTE( Synthetic Minority Oversampling Technique) for class balancing such ...
2
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0answers
378 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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617 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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23 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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0answers
79 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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0answers
93 views

dealing with imbalanced data set in multiclass text classification

I need to build a text classification model. I have a labeled training set and my goal is to classify the new unlabeled text . My training set is composed on 6 categories, that are imbalanced. The ...
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0answers
18 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
38 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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111 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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0answers
34 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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88 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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177 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) ...
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0answers
89 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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115 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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216 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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24 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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16 views

Need advice on unbalanced time-series dataset, for use with CAPM regression

I have 40 years of monthly historical returns of around 3000 mutual funds. The dataset contains both active and inactive funds, so some funds have data for the whole period, whereas others will have ...
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16 views

softmax in nnet with cost function

I have 40 classes in a classification problem. I'm using nnet with softmax but since the classes are very imbalanced I get the same probabilities for every case to predict. I read about F1 score. Is ...
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0answers
9 views

(logistic regression with imbalanced data) Does high polynomial degree in combination with rebalancing negatively affect accuracy?

Data Set: https://www.kaggle.com/c/GiveMeSomeCredit/data (cs-training.csv) Training Tool: Weka Data Processing Tool: Python (for higher polynomial degree) Question: Balancing data (by down sampling ...
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40 views

Sampling, feature selection and preprocessing in cross validation

To brief my question, I want to clarify the order of parameter tuning and the correctness of the flow in my scheme. In my classification scheme, there are several steps including: SMOTE (Synthetic ...
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0answers
17 views

What type of curve to use in object detection task to measure performance of detector?

I have an object detection task with one object type(one object type + background = object detection with sliding window as binary classification of each window). And my data is unbalanced(many ...
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0answers
58 views

Balancing random forest via cross validation. Difference between sample weight and cutoffs?

My random forest model of a simple binary target (0, 1) and is producing unbalanced results. i.e many more false positives than there are false negatives. In addition, '1' is a low percentage class, ...
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14 views

Model variables don't match stratification variables

Okay, so here's a puzzle that I recently encountered. Suppose I am interested in modeling a treatment effect (measured as a continuous variable) on a population, stratifying on a dichotomous ...
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14 views

Scaling before class rebalancing or after?

I'm training an SVM on my train data, which I'm then trying on my test data to find the accuracy of the algorithm. Would it normally be best to rebalance the class imbalance (2 classes with 60/40 ...
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85 views

Nested ANOVA with 3 random effects and unbalanced design

I would like to run a nested ANOVA to test three random effects (secteur, loc nested in secteur, site nested in loc) on the variable A. The design is unbalanced so I used lmer instead of aov. However, ...
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0answers
40 views

Classification Algorithm For Small Sample Sizes

I am looking at a problem now where I need to train a classification algorithm. There are only 2 classes, lets call them A and B, and I want a value between zero and one indicating the probability ...
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0answers
114 views

Optimize Probability Thresholds for class imbalances in glmnet models in caret

In direct relation to the topic discussed here I intend to retrain the model in order to optimize the probability threshold for classification of both classes. Currently the model achieves high ...
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0answers
41 views

unbalanced groups in mixed design ANOVA

I want to perform a mixed design ANOVA. Time is the within subjects factor and the between subjects factor is Borderline, which is a categorical variable (borderline yes or no). There are 30 people ...
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0answers
15 views

Non idependence within groups

I have to train a machine learning model for classifying two groups. Unfortunately, my positive group has a small number and many cases are not independent from each other (observations taken in ...
0
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0answers
119 views

Best machine learning methtod for classificating datasets with non-independent cases within the groups

I have to perform binary classification of my data with supervised machine learning, but I have some difficulties working with my data set. It consists many genetic mutations that have parameters ...
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0answers
51 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 ...
0
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0answers
12 views

comparing probability of imbalance classes

I am trying to figure out what id the standard way to compare the probability of occurrence of two imbalances classes: let say there 1500 web pages with different languages edition (e.g. Wikipedia). ...
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0answers
75 views

cost matrix, unbalanced class, oversampling and threshold probability

Let's suppose I have a cost matrix with TP=+90 FP=-10 TN=0 and FN=-10, and that the class is unbalanced. I need to capture the costs in my decision. To do so, I always consider the probability ...
0
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0answers
60 views

SVM One-vs-One vs One-vs-ALL SVM

For an unbalanced dataset annotated by human annotators in which each item is assigned to different classes, what is the argument for and against using any of One-vs-One vs One-vs-ALL SVM ...
0
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0answers
190 views

Any advice on how to improve my accuracy rate in text classification?

I'm trying to do a text classification task. Here are some specs: Context file size = 1M+ documents already labeled Number of top-labels = 17 Number of sub-labels = around 130 Each document is ...
0
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0answers
150 views

unary classification in PyBrain

I've just started using PyBrain for some data classification work, and I've gotten it working pretty well where I have data from all possible classes and I can train the network using all the classes. ...
0
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0answers
100 views

Unbalanced groups in a Hierarchical Linear Model

I would appreciate some practical and/or conceptual advice on sample sizes in a two level hierarchical linear model. A lot of the material on sample sizes and HLM is about the number of level 2 ...
0
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0answers
1k views

One-way ANOVA with unequal sample sizes

I have a function for performing one-way ANOVA in R: ...
0
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0answers
29 views

Comparing networks of groups of unequal size

I want to compare some network properties such as entropy, connectivity, etc., between 2 groups. I have time series fMRI data on patients (n = 80) and controls (n = 30) for certain regions of the ...
0
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0answers
113 views

Repeated Measures ANOVA or mixed model? And with massive group differences?

I need some guidance on which statistical test to use: I want to know if the nature of frog calls changes depending on the time of day. I observed 4 species of frogs at the same 3 times for several ...
0
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0answers
186 views

Interpreting coefficients for random effects models with extremely unbalanced data

I'm currently working with a data set that has numerous samples collected over time at different sites in a study area, and I'm interested in detecting a trend over time for that area. I know that in ...