Questions tagged [classification]

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 variable behavior which can be studied by statistics.

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9 views

How to handle overlapping classes

I am working on the classification of a dataset which contains ambiguous and noisy data - the result of which means I have class overlap in the feature space. There seems to be a few papers on this ...
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LibSVM - Multi class classification with unbalanced data

I tried to play with libsvm and 3D descriptors in order to perform object recognition. So far I have 7 categories of objects and for each category I have its number of objects (and its pourcentage) : ...
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Is classification using linear regression called logistic regression or linear disriminant analysis?

I have heard people describe logistic regression as linear regression except as it is deployed for classification. But I have heard the exact same comment about LDA (linear discriminant analysis). Out ...
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Genetic algorithm (GA) for training a generalized linear discriminate classifier

How can genetic algorithms (GA) be used for training a generalized linear discriminate classifier? What would the genes/chromosomes and fitness function be? How can genetic programming (GP) be used ...
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Classification for some rare events

I am seeking advice for classification methodology. I have ~1 million samples, less than 1000 features (I could reduce to about 10 features that I can guess are more useful than others) and real ...
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What is MBConv that EfficientNetv2 is using?

EfficinetNetV2 uses MBConv/Fused-MBConv as a part of it's architecture. There is no clarity of what these operations actually are from the paper (nor from the references). It appears that it is some ...
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How to do low scale logistic regression?

Let's I have data on 10 customers. For example, I have their Age, gender, income, marital status and whether they bought a car or not. Now I have another new customer data. How can I predict/find out ...
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How to do low scale time series prediction?

I have a small time series data with 10 observations Each observation is spaced at 20 days gap For example, I have sales revenue from day 1, day 21, day 41, day 61 till day 221... Now I would like to ...
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Combining one class classifiers to do multi-class classification

I am working on a 3-class classification problem. The classifier I'm using is Bayesian Networks which provides me with a classification accuracy of around 60%. When I do a two-class classification, I ...
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how does class 0 scores in the classification report are calculated ( sklearn python )?

Here how these class-0 probability are calculated?? print(classification_report(y_true, y_pred, target_names=target_names)) precision recall f1-score support ...
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How does MATLAB Computes the Negated average binary Loss?

I want to know how MATLAB computes the Negated Average Loss that is provided by the predict(__) function, I have an multi class (OneVSAll)SVM classifier and it uses the hinge loss, given the ...
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what should i choose classificator for hard-to-separate data

I have the task to classify wheat and non-wheat agriculture by VI index. Example data in R. (Not sure if it's highly reproducible ) ...
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Why do I have the same validation accuracy for every epoch? [duplicate]

I developed a CNN for ECG arrhythmia classification and when I train the model I obtain the same validation accuracy for all of the 50 epoch. Can you please tell me what is wrong? I tried to modify ...
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1answer
686 views

How to use data_utils.WeightedRandomSampler and still be able shuffle training data in Pytorch?

I am working on the multi-label classification task in Pytorch and I have imbalanced data in my model, therefore I use data_utils.WeightedRandomSampler method ...
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1answer
198 views

WoE for Random Forest and SVM

There are a lot written about WoE (Weight of Evidence) transformation for the case of Logistic Regression Classifier. It works great. The question: can one (or does it make sense) to use this WoE ...
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Test Accuracy lower than train and validation accuracy in Binary Classification - Random Forest

I started working on a Binary classification problem recently. My dataset contains 300K records and is fairly balanced.(60%(0) & 40%(1)).I trained different classifiers for doing the task at hand. ...
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2answers
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Selecting multiple hyper-parameters via successive nested cross-validation

Selecting multiple hyper-parameters via successive nested cross-validation I am currently working in a classification task on motion data. Each sample to classify is represented by a set of features ...
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Can you use SVMs with strongly biased sample sizes?

I want to use linear SVMs to classify two groups of objects based on ten features. However, I have a strong imbalance in group sizes with one group having a bit more than 90% of the cases. I have ...
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1answer
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Classification of data tables (each table is an item)

I have to work on a binary classification task where single items to be classified are not single rows of a data matrix, but groups of rows. In other words, I have $N$ data tables of varying size $n_i ...
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Baseline Risk in XGBoost Model

I am doing a project to predict negative clinical outcomes after surgery using logistic regression and xgboost. Upon testing a few sample patients, I see that oftentimes the xgboost model predicts a ...
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1answer
301 views

Tensor Classification Models

Aside from Convolution Neural Networks, are there any other methods that allow for classification of Tensors? My observations consist of multi-dimensional tensors with height of 1, where each channel ...
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Neural network that outputs correctness estimate of another network

Basically, considering MobileNet as the main neural network, I want to create a complementary network which will take as input raw images and output the probability that the main model ouputs the ...
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Road and side walk classification

I would like to share some thoughts about a problem I am facing. I need to detect the moments when the cyclist aren't riding on the road (sidewalk, for example). The video is recorded from a camera on ...
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Linear discriminant analysis for non-normal data

I have a classification problem in which the independent variables are not normally distributed. Is it appropriate to apply linear discriminant analysis for classification? Since lda assumes data to ...
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Clustering spatial data [closed]

Suppose a set of approximately 350 elements. Each element is represented by a matrix of 16x16 values, as shown in figure. My aim is to group elements based on the similarity of the matrices. To give ...
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1answer
435 views

Available methods for classifying long text sequences in NLP

I am looking to solve a multi-class classification problem with long sequences of text with some rows having 1000's of tokens. Some of the state of the art methods such as BERT have a token limit and ...
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1answer
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Probability of guessing True when the target is True in a multi-label classification problem?

I will try to explain what I am trying to ask in my terms because I don't know how to do any better. Feel free to edit for clarity if you understand better than I do what I am trying to ask. The ...
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Imbalanced classess and how to deal with them

I am taking my first steps in machine learning and data science area. I know for sure that my next task will be related to the imbalanced class problem. I’ve walked through many articles covering this ...
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Simple Decision Rule outperforms ML methods [closed]

I want to predict a class out of $n$ possible classes. I have a feature vector of length $n$, each value representing the value (all between 0 and 1) for its corresponding class. See an example of a ...
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1answer
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Partitioning with cross validation

I am new to data analytics having only started exploring the field this week. I have downloaded KNIME and am working with a single dataset to try out different classification algorithms. I am ...
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1answer
73 views

Is it trivial to train a NN to classify numbers as integers or non-integers?

I understand that the data type of the inputs would have to be the same, but say that I have all of the numbers as floats with two decimals. Would a neural network be able to learn the classification: ...
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Example of scenario where first split does not improve gini impurity

Suppose one uses gini impurity to find the best split while constructing the classification tree. Give an example of a scenario where the first best split does not improve the gini impurity compared ...
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Problem with Converting my LSTM Multi-class Classification Model to a Binary Classification Model

I am a PyTorch newbie and trying to learn by following tutorials. I have implemented a model for a multi-class classification task and now I'd like to use this model for a binary classification task. ...
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RNN Sequence Prediction - Am I Introducing Leakage?

I am training an LSTM for sequence prediction where the targets are either 0 or 1 and I am currently using a sequence length of $20$. I have done extensive feature engineering so I have 61 input ...
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1answer
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Correct cross-validation procedure for single model applied to panel data

Questions What is the correct CV procedure for panel data? I've been thinking of the problem as cross-validating a model fit to multiple time series data. Is the "population informed" CV procedure ...
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Why is the optimal cutoff for AUC different from that of specificity in this simulation?

I am working on a binary classification problem on an imbalanced data where the majority class is about 90% 'no' and the minority class is about 10% 'yes' of the total data. Iteration 1: I randomly ...
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1answer
201 views

Range of values for hyperparameters of the KNN

Algorithm : Classification by k-nearest neighbors with Euclidean distance (neighbors.KNeighborsClassifier). Determine the important hyperparameters (2 maximum) that can significantly influence ...
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1answer
215 views

Classifying a text into question or answer

I'm searching for a library or tool that allows me to classify emails of a mailing list into what mails are very likely questions and what mails are very likely answers. Can anybody recommend such a ...
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Is predict_proba() reliable for SVC?

I want to implement some kind of confidence measure for my stock prediction model, which predicts the next day's trend (whether the price would rise or fall). As in, a trade order should be placed ...
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1answer
168 views

Almost all predictions of a SVM are positives(or are all negatives)

I'm facing a binary classification problem using svm light. However using 5-fold-validation I noticed that later I train SVM with training set (Half positive and half negative samples about) the ...
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22 views

How to predict multiple events at multiple time points in future?

I have a public EHR dataset which contains info on a) lab tests b) diagnosis c) surgical procedures d) drugs prescribed etc Now, using the above data elements, I would like to predict the below a) ...
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1answer
18 views

Comparability of classifier probabiliy estimates

Consider that you have 3 classification models ($model_1$, $model_2$ and $model_3$) that are designed to model whether or not customers are interested in different products of your company (binary ...
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1answer
495 views

A statistical test to measure the importance of features?

I'm currently trying to assess importance of the features for my classifier. The situation is the following: first I train my classifier with all of the features I have and tested on a test set . Then ...
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1answer
2k views

Improve precision/recall for class imbalance?

Trying to get better precision/recall for both classes ... any tips? I have heterogeneous features [a few num vars, a few cat vars, and 2 text vars] Target is a binary classification w/ class ...
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Comparing accuracies from various ML algorithms

Nowadays, many articles propose to compare various machine learning methods for classification purposes, in order to find which method is best suited to a specific research question. Most of the time ...
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1answer
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validation accuracy, recall and precision remains constant after 30th epoch

I am using TensorFlow model EfficientNetB0 for transfer learning, but after a number of epochs the validation accuracy, -precision, and -recall remains constant. Is this something I should be worried ...
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SVM convex optimisation - What is the role of duality

Consider the support vector classifier problem with slack variables $\xi_i$. In a reference book (Elements of Statistical Learning, Hastie et al) I am using, the authors first introduced the convex ...
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Point pattern classification with spatstat: ist this a valid way?

I’am trying to classify bivariate point patterns into groups using spatstat. The patterns are derived from the whole slide images of lymph nodes with cancer. I’ve trained a neural network to recognize ...
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1answer
56 views

Why use RBF kernel if less is needed?

I have seen online theorem's such as Cover's theorem Wikipedia which prove how given $p$ points in $\mathbb{R}^N$ the linear separability is almost certain as the fraction $\dfrac{p}{N}$ is kept close ...

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