Questions tagged [classification]

An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

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Can tanh be used as an output for a binary classifier?

I am creating a binary classifier in Keras and here;s the code ...
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How To Perform Time Series Data Patterns Classification

I'm fairly new to Python, and I want to create a Machine Learning algorithm that classifies Time Series Data Patterns. The data I will be using comes from an accelerometer-arduino system fashioned ...
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Product classification based on Description of a product in eCommerce website

I am searching for an eCommerce dataset which should have a product category and description for my academic research in Machine learning. Please suggest any public dataset available. INPUT: UNIONBAY ...
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Feature addition/ subtraction and SVM model accuracy

I am working on a text classification problem where I want to improve the accuracy of my model. I am presently using SVM with linear SVC and OneVsRestClassifier. The model should correctly predict all ...
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How can I stack one feature-engineering based model and another one non-feature engineering based model in python?

I have a StackOverflow question answer dataset. ( this is a classification problem ) So , far I have created two different models. Model 1: LightGBM model optimized. Data fed into LightGBM model ...
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Modeling strategy for predicting a day/hour based on my dataset

This is my first time posting here. I'm usually on SO. So I'm not sure if these kind of questions fit into DS stackexchange. I genuinely need opinions on this. What data do I have - ...
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what are possible error analysis approach in tabular data?

I am working on binary classification on tabular data. The dataset is mostly made of categorical data and after fitting the data to a model I found test accuracy to be low. I want to do error analysis ...
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Neural network approaches for classification of time signals

I have 3D images that constitute of 2 spatial dimensions, e.g. (x,y) coordinates, with the 3rd dimension being a time signal. The signal is not periodical, but related to physical properties of medium ...
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ROC curve and optimal threshold

I am doing a practice problem predicting a binary outcome. I have plotted an ROC curve and found the optimal threshold percentage to call future predicted observations a 1. I see that this threshold ...
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Classification training using probabilites and not raw classes (factors)

I have a problem where instead of having classes, i.e. a vector of 0s and 1s, I have the probability of an observation belonging to a class. A vector with 0.1, 0.95, 0.2, 0.3, etc. The obvious ...
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How can I imporve accuracy for text classification and mapping using SVM?

I am working on a problem where I need to predict the text corresponding to another text in my training data file. For example: if I have value like the software in one of my columns and another ...
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How to predict the value in KNN?

I am trying to build the KNN algorithm for IRIS dataset. First, I've computed the distance and stored it in 1d array. However, I am really struggling to build the prediction function. Therefore two ...
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Merging three different customer segmentation systems into one

I have been given a task where I have three existing customer segmentation systems (rule based e.g. if customer spends X in Y amount of time AND whatever then put in top spender segment is one segment,...
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what are effects of working with categorical dataset

I am working on classification problem where the dataset contains 90% of features as categorical. It is binary classification problem, and the class is heavily imbalanced. I performed Smote over ...
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how to work with NLP with other features

My dataset looks like this ...
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Adding machine learning classifier at the end of CNN layer

I wanted to use the CNN as feature extractor for my images and then fed these features to some machine learning classifiers such as SVM, decision tree and KNN. However when I was trying with SVM I got ...
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How do I interpret the given classification report?

The given classification report was obtained from running a Random Forest binary classifier on the test data. There is huge class imbalance in the training data. How do I interpret the given ...
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Probability calibration is worsening my model performance

I'm using RandomForest and XGBoost for binary classification, and my task is to predict probabilities for each class. Since tree-based models are bad with outputting usable probabilities, i imported ...
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Classification and prediction on binary data

I am trying to cluster a binary data that consists of 294 inputs and 120 possible outputs. I have tried to train a neural network using tensorflow/keras with the sigmoid function as the activation one....
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Hybrid classification neural network

I have product data and I need to classify products to categories (for example Lenovo laptop to Laptops category, etc.), each product has properties such as: description list with image URLs (...
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What machine learning algorithm should I use for specific user configuration?

I have a data-set that contains thousands of employee data, including their role, department (Applications Developer, IT Support, Network Management etc.), and using one-hot encoding all of the ...
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What are the 'easier' option for LSTM?

I am currently working on rare event prediction, which I have never done before (I used to work with simple prediction problem), and I looked up on this article about using LSTM for time series rare ...
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Multivariate time series prediction with binary target

I have an electronic component whose sensors record temperature, current and voltage values of various sub-elements. These readings are taken at regular intervals of time and I organized them as ...
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How do I deal with missing values in a data set?

I am trying to build a binary classification model which predicts whether a patient would me infected with a certain disease at the the end of his hospital stay or not. The features that I have are ...
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Why doesn't the binary classification log loss formula make it explicit that natural log is being used?

I'm completing a DataCamp course where we are introduced to the log loss formula for binary classification: Two scenarios are given to show how the formula is used. One with p=0.1 and one with p=0.5....
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Using deep-learning on graph data for binary classification

The data: I have certain data that I decided to represent it as a graph (I thought it would suit). So I have the weighted graph data that includes a numeric attribute for each node. (networkx graphs)....
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When I use SHAP for classification problem, it shows an output that is not 0 or 1. How can I overcome this?

I'm using Pima Indians Diabetes Database(https://www.kaggle.com/uciml/pima-indians-diabetes-database). I made predictions using XGboost and I'm trying to analyze the features using SHAP. However ...
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Is there a way to choose obtain an optimal threshold to maximise F1 measure using ROC?

I am trying to choose the best threshold for a binary classification problem that maximises F1 measure. Currently, I am manually analysing the F1 measure at thresholds 0.1-0.9 in steps of 0.1. I am ...
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Probability vs recall for time series classification task

I am working on the time series classification task that focuses on predicting a fault. I framed the problem as a multi-step forecasting problem, where my goal is to predict to the class at ...
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Is it normal that a classifier always wrongly predicts the same samples?

I'm trying to improve the accuracy of a classifier, a random forest one. I built different models with the same hyperparameters but with different random seeds, trained them with the same training ...
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Can i use survival analysis to predict if a person will “die” or not, and then get the survival time if the person does?

I want to determine, given a project, "How long will it take for this project to be successful ?" Therefore, survival analysis seems like a perfect fit in this case (as I do have some projects that ...
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Random Forest Prediction

Let's say I want to classify if the employee will churn or not. In my random forest, I have 6 estimators where 3 of them predict the employee to churn and the other estimators predict the employee to ...
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Can we vectorize nominal text feature using tfidf or count vectorizer?

I recently participated in the hackathon. The dataset includes drug name, sentiments about the drug, unique id. The target variable is the sentiment. It was a sentiment classification or analysis ...
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Blind feature engineering

I received a dataset for analysis that had ~100 numeric columns with anonymous column names(X1, X2, X3, etc...) and asked to do a binary classification. My resulting classification algorithm using a ...
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Reconize a card from a video stream

I want to make an mobile app where you scan using the camera and it gives you the card you just scanned. (from a board game) I got a PNG of each and every single existing cards, but I don't really ...
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What are the latest and most succesful classification algorithms at the moment?

I have googled this for some time with no luck. All i get are tutorials or articles explaining the classic algorithms like linear regression, random forest, etc. I would like to know which are the ...
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What type of classification algorithm for recognizing events in a set of data?

I would like to know what type of machine learning to use for recognizing events in a set of data. (or at least be pointed in the right direction so I can do my own research on the topic.) I'm trying ...
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Confusion on result of K-Fold Cross Validation and Independent Test set

I am relatively new in Machine Learning. I am using Random Forest and SVM for a project. Where I did a ...
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SVC classification not working at all on MNIST dataset

I'm sure I probably did something stupid but I'm trying to fit a simple SVC classifier on MNIST dataset as an example, and it completely failed by only predicting result 1 (sometimes 7 depends on how ...
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Are more classes more favorable than a single combined class?

Imagine the following scenario. Train a classifier that classifies an object into one of these n+m classes: ...
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XGBOOST : model.predict_proba() and model.predict() conflicting behaviour

I have two classes : 1 and 2 The output of model.predict_proba() -> [0.333,0.6667] The output of model.predict() -> 1 This is happening for around 200 test values out of the test data of 10 lac. ...
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How to find what events cluster together?

I have a data set that looks at a five-year timespan of peoples' lives and indicates if specific events have occurred (Divorce, Birth of Child, Health Shock, etc.). ...
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Implementing Data Catalog from scratch

I have a requirement of ingesting huge amount of user specific data and then searching on it. Trying to be low cost solution, I am leaning towards creating Kafka based ingestion pipelines and ...
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How significant the variables like “id”, “region code” etc are in the predictive modelling?

I participated in one of the hackathon. And there the variables were like id, region, gender, age .etc. It was a regression problem. I did scaling on the variables. But I am not sure what to do with ...
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Significance of AUC score

My model (Logistic Regression) has AUC score of 0.8 Am I right in stating that the probability of the model ranking a random positive sample higher than a random negative sample is 0.8? Also, how ...
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Convolutional Neural Network for Binary Classification: Flipping Classes

I've got a CNN (resnet18), performing binary classification. The final layer is fully connected with 2 nodes. The loss function is CrossEntropyLoss (pytorch). When I switch the labels of the classes (...
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How to modify display loss function for the Vectorised Feedforward network?

I was practicing vectorising the baackprop for a basic NN and I tried modifying a code for binary classification which was originally written for multi class classification. Code: ...
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In the context of natural language processing, can anyone give a concrete example of True Positive, True Negative, False Positive, False Negative?

Google post gives a interesting explanation about True Positive, True Negative, False Positive, False Negative True Positive (TP): Reality: A wolf threatened. Shepherd said: "Wolf." Outcome: ...
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Intent Classification with imbalanced dataset

I am trying to train my ML model to classify 13 intents. Prior to training the model, the training data was sufficiently accurate. Here are the imbalanced training data sizes per class (class_num: ...
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XGBoost, binary classification: uneven number of observations per user

I'm working on a binary classification problem with XGBoost and I have a dataset, which has uneven number of observations per user. For some users there are over 100 observations, whereas for some ...