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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13 views

Any ideas on how to segment a 2D vector field?

I am given a 2D vector field and a ROI out of which I sample a random number of n FLOAT vectors of the form (x, y, dx, dy). What could be good ideas to classify each of these vectors in any of two ...
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Understanding the Johnson-Neyman algorithm for finding the region of significance in a trivariate correlation analysis

I'm pretty new to the whole statistics world, so excuse me for being a novice in advance. I'm trying to understand Andrew F. Hayes's PROCESS macro in SPSS [1]. To my best understanding, the macro uses ...
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Solving for the discriminant function in LDA

This is related to the question posted in: The discriminant function in linear discriminant analysis In the one dimensional case, where $p_k(x) = \dfrac{f_k(x)\pi_k}{P(X = x)}$, where $f_k(x) = \...
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Is there any classification algorithm that doesn't give probability?

I'm studying the ROC Curve, and I was wondering if there is any classification algorithm that doesn't return the output class as a result of a certain threshold from the probabilities of the algo? ...
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19 views

Using target variable in training process

I am dealing with a task where I train a classification model to predict whether an item is going to be returned in a web shop. Can I use features which contain information from the target variable? ...
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instability of logistic regression

I am reading Introduction to Statistical Learning and it is said (as in other websites) that Logistic Regression is unstable compared to Linear Discriminant Analysis in well separated cases. ...
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Interaction between Average Precision metric and prior probabilities

Reading the paper CNN Architectures for Large-Scale Audio Classification I found this statement: AP is widely used as an indicator of precision that does not require a particular retrieval list ...
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Select features first or optimize hyperparameters first?

I want to train a binary classification model using some tree ensemble (either xgboost or random forests). My dataset has some 50 features, and I believe some of them are redundant (there's ...
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Tensorflow classification model - Training data questions

I am working on a classification problem. I have a set of data that is classified to different hierarchies . As an example we could have Description: whole grain brown bread with seeds 12 slices ...
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20 views

Using multiple neural nets in sequence on one classification problem

I'm working on a time-series (comm signals) classification problem that has 25 possible classes. I have one fairly deep CNN that can perform fairly well on this problem, but I'm hoping to make better. ...
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Cannot use SVM with RBF Kernel

I'm new in R. I have an original dataset with 25771 variables and 118 samples. I already performed feature selection and split the dataset into 70 30 so i have 82 samples in my training data and 36 in ...
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Adding a prior to BERT text classifier

I would like to train a BERT model for intent detection. However, I would like the model’s intent prediction to consider the previous intents (or maybe just the most recent) during the interaction. ...
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Balanced Classes Performing Worse than Imbalance Classes

I am training a model on a data set that has imbalanced classes; 97% of the labels are 0 and 3% are 1s. I chose to upsample the data in order to make the classes equal in the model training. When I ...
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Which are the training examples in a sequence classification?

I am implementing a Sequence-to-Sequence Classification in Matlab. As an example here it is the documentation from mathworks: https://it.mathworks.com/help/deeplearning/examples/sequence-to-sequence-...
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How to apply PCA on 3 dimensional image data in python

I have dataset containing colored images of cancerous and non-cancerous tissue cells. The image dimensions are 50x50x3, and I have a total of 280,000 images. I want to apply PCA to it in order to ...
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32 views

Y-axis value (class probability) more than 1 in a Random Forest PDP

Sometimes I am getting such PDPs from a Random Forest classification (two-class) model. Why Y-axis probability is more than 1 here? What might have caused it?
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Convergence analysis of fine tuning or transfer learning

Fine-tuning is the process of using a pre-trained model (corresponding to an old dataset) for learning a new task (for a new dataset). I have looked a lot but could not find a convergence analysis for ...
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what is the difference between Naive Bayes and NON-Naive Bayes?

In Naive Bayes Why is it necessary for Naive to assumes that the input features are independent and not co-related . can anyone explain with a very simple example on what is the problem of events ...
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What kind of model can predict propensity to adopt a new service?

I've been thinking about an interesting business problem recently: I've started offering a new service to my customers, and I'm looking to build a model that can predict which of my existing customers ...
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Which ml model for selecting one candidate among many

I have an entity matching task and I am struggling to decide which ml model I should use for it. Let me break it down. I have a complex search query, and for each query I can have from 0 to ~50 ...
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Performance metric for continuous binary classification method

I have and imbalanced data set with two classes of data: $A$ and $B$. I apply a method that assigns a continuous probability to each element of belonging to class $A$: $P_{A}$ , where $P_B=1-P_A$. I ...
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Assigning different COST for each event in a classification model

I need some help with a project (described below) for a banking client. Any advice/suggestions would be greatly appreciated. Project : We are trying to model credit card attritions. The event rate ...
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Improving accuracy of multi-class text classifier

I am trying to build a text classifier with 4 highly imbalanced classes. Data has around 4000 documents and highly sparse. I have used XGboost and few other algorithms.Highest accuracy is given by ...
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Can we compare class probabilities between different methods in caret?

I am using the caret package in R for binary classification and I want to compare different methods (e.g., random forest, SVM, ANN, PLS-DA...). I consider the class probabilities as a "certainty score"...
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Predict for an outcome within a time window

I have a dataset which has around 10K records. My objective is to predict whether the customer will churn or not. Binary classification problem with each class representing around 55:45 proportion ...
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drop features with one class zero variance

If a feature has zero variance, then it makes sence to drop it as is it has no predictive power. What if a feature has zero variance only for cases that belong to one class but not in the other (...
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Should I put both continuous and discrete variables as a model output? [closed]

I wanna predict several variables in a dataset and some of them r categorical and some contenious idk whether it's safe to predict both types at the same time coz it's a mix of regression and ...
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Classification: when part of independent input variable is a constraint [closed]

I had this setup of dataset for classification, where during the training stage on the old data, certain constraints are not factor into the model, however, at predictions, I will like to know if ...
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How to convert SVM values into corresponding class type?

I am doing SVM on R, and when I do: ...
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Classification - deterministic to probabilistic

Let $\mathcal{M} = \{X_1 , ... , X_N\}$ be a collection of objects, and assume that $x = X_i$. Imagine that we cannot observe $x$ directly, but we do have measurements $y = y(x)$ (only 1 dataset, ...
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Why 1 out of 5 AUC cross validation score is very low?

I am using xgboost model for binary classification problem. I am using 5 fold cross-validation (stratified as class imbalance) which results into the following. ...
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Is this a good modeling approach? [closed]

I have a mixed data with countinous target variable , i tried regression method but it gaves me low R² and a very high MSE , im thinking of taking this approach where i take the numerical data with ...
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Probability as the Correct Term for Classifier Scores

This is more of a semantic question, but is the term probability, in the strictest sense, the correct term to use when describing the output of a predictive model that outputs values between 0 and 1? ...
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Convnet learning: all weights tend to zero and left only with bias

I am working on a conv net that deals with a classification problem and wonder what sort of mistake I am making to get this sort of problem? I have nine outputs - I can't use softmax as the nature of ...
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Was Amazon's AI tool, more than human recruiters, biased against women?

A typical example how bias in data is being copied by AI is Amazon's recruiting tool that got abandoned in 2018. In the various reports it is implicitly (or sometimes explicitly) stated that the AI ...
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What algorithm to use for fitting several different lines

I have a unique problem I'm not sure how to approach. I have some data. The data was generated by a function that's basically $k$ different lines ($k$ may or may not be given). Example: However, ...
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Compute correlation between pairs of attributes for each class label

I am working on collecting some dataset characteristics for binary classification tasks, and I want to calculate the correlation following the measure proposed by this quote: The correlations ...
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What is the notion of confidence in multi label classification?

For a single label classification, the notion of confidence is easy to understand. If the classifier has 80% confidence for 100 data points, in 80 of them the predicted label should match the actual ...
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Predicting a breakdown probability in a time window using machine learning classification in Python

I want to predict breakdowns of a machine. The data I have is on a daily basis and contains info like "minutes in operation", "number of external shocks" or "operator name". I created additional ...
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Creating robust intervals from highly skewed data?

I am using factor analysis to model the underlying structure of social capital. My data consists of individual responses expressing how often they interacted with other individuals in a specific year, ...
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Binary Classification Propensity Scoring: High Accuracy in Train/Validation/Test, but Low Accuracy on Production Data

Before I describe my problem, if anyone has material for propensity scoring I would love it if you posted some. I've done a lot of research on propensity, but I think I've bled myself dry on the net. ...
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Is PCA suitable to validate an a priori remote sensing categorization of trees?

I have an a priori (on-screen digitalizing) classification of (1) old trees (detected present in a 1967 satellite image before alleged planting schemes) and (2) new trees (planted trees detected after ...
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Interpret several classifications to one classification result

I want to interpret several data series X, that consist of like 4 to 20 values that can range from 1 to 5. Imagine these as a result of classifications, where each row is a different id, and each ...
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Is variable standardization not required when using logistic regression, decision trees or random forest algorithms?

I am trying to run several classifiers on the Customer churn dataset (https://www.kaggle.com/shrutimechlearn/churn-modelling#Churn_Modelling.csv). There are several variables that are on a different ...
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Comparing multiple numeric vectors by ranks

I've been recently looking into multiple classifier comparison, and it seems the works of Demsar (2008) remain state-of-the-art in this field. Let $u_1$,$u_2$ and $u_3$ represent three real valued ...
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How to use additional non-visual data for image classification?

I've got a Resnet network that classifies images into n classes and is working fine. I want to boost its performance buy using additional information I have regarding the images. This info comes in ...
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Is there a name for this visualization technique (binary classification)?

I'm working on a binary classification problem with class labels $Y \in {0, 1}$, and have a classifier that emits the probability $P(Y=1|X=x)$ for each test example $x$. To summarize the performance ...
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Linear discriminant analysis accuracy issues

I have generated a normally distributed sample along with 3 classes to perform classification. I got very low accuracy. I was wondering if you could give me your valuable feedback to improve my LDA ...
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Do i need to use hyperparameters from gridSearch on whole training set to get final model?

I just want to make sure i am on the right lines so please correct me if wrong. I am testing which hyperparmets are best for logisitic regession on my data X, y where X is featrues and y is target. X, ...
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How can I create a predictive model based on monthly customer usage data to identify risk thresholds for future churn?

What methods would be suggested to build a predictive model in Python using the below data set to identify customers who are at risk of churning in the future? Data Set customer-id - unique customer ...

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