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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How to interpretmulti-class confusion matrix?

I'm looking at the SAMHSA Mental Health Client-Level dataset. I did some t-SNE plots (dropping irrelevant cols, normalizing some, one-hot encoding some) of 500k rows out of 6.5mil. I'm trying to do ...
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Find closest color class to an RGB value

I have a module that estimates the color of an object and returns an RGB value in this format: (40, 48, 68) which corresponds to this color: Now I have to classify ...
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Why is my LSTM model not predicting well when predicting labels for a new dataset?

I have a 15 timeseries datasets with 25-30 columns and is labeled by following a complex formula applied on the 25-30 columns. When training, I split the datasets as training datasets and unseen ...
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PR-AUC vs F1 vs Balanced Accuracy

I'm trying to create a Random Forest Classifier for selecting ~ 700 features. I have a highly imbalanced dataset to select features from. There are significantly fewer positive cases (1%) compared ...
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Robustness and Sensitivity of Naive Bayes to Irrelevant Features

I understand that one of the strengths of Naive Bayes is its robustness to irrelevant features. However, it's also important to note that it can be sensitive to the presence of irrelevant features, ...
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How can I scale my data for a machine learning model in a way that preserves the relationship between columns?

Lets take a simple database with 3 columns called x1, x2 and label for example label is being labeled by this condition if x1-x2> 0 then label = 1 else 0 , i.e <...
Rushabh Kheni's user avatar
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Why my simple resnet model overfit?

I work on data classification. My train results are good 90%+ accuracy, but the test accuracy/loss is inconsistent. I don't succeed to get rid of the overfitting. The images are grouped, so to ...
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Are there specific properties in the area of intersections in a multiclass support vector machine one vs one or one vs rest classification problem?

For visualization what I mean in a 2D space.
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i am trying to get the the variance of derivative of order 2. i only have the data of an EEG signal sampled at 128 Hz. is the below code correct

I basically want to implement equation 7 present in the added image interpolation=CubicSpline(x,y) x_interp = np.linspace(0, 1, 129) y_interp = interpolation(x_interp,2) var=np.var(y_interp) df=((np....
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How to take the $\log$ of $e$ when taken to the power of a matrix?

I'm having some troubles trying to solve the following question, I'm trying to find the $C$ which maximizes $$\begin{align}\text{arg max}_{1\geq m\geq K}(\log p(\mathbf{x}|C_m)+log P(C_m))\end{align}$$...
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Each person gets their top, or second choice of activity over a period of 6 slots

We are running a camp for 130 children, and on 3 days they can pick different activities to do. One activities for slot 1 (45min), the other for slot 2 (another 45min), enabling them to do 6 ...
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Why do object detection model adversarial masks look different from those of image classifiers?

I was messing around to observe the behavior for adversarial attacks on image classifiers, and decided to try it with an object detector as well. I realize that inference time attacks are more complex ...
Soumil Datta's user avatar
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How to optimize my CNN classification architecture

I have this CNN based model architecture that takes an RGB image. Now I'm trying to change it for a color classification case on an object (10 color classes: white, black, yellow, etc). This current ...
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Is it possible to have different amount of features for the Classification decision in a support vector machine?

Is it possible to train a support vector machine with two classes using two features and then trying to make a decision for a new data object to which class it belongs that has the same two features ...
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How to Yield a Better AUC / Lift Score?

I have a dataset with 200k records and 173 features focused on binary classification. Class proportion is around 98.7:1.3 (1.3% target=1). Currently, I am trying to increase the performance of my ...
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Which dataset could be a good choice to train Environment Sound Classification model for user environment awareness while wearing earbus?

Which dataset could be a good choice to train an Environment Sound Classification model for the following use case: use the model in the earbuds/earphones to detect important sound events in the user'...
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What feature selection method is best for a multi class classification problem with one-hot-encoded columns?

I am trying to solve a multi-class classification involving prediction the outcome of a football match (target variable = Win, Lose or Draw). With a dataset of 2280 rows, which is 6 seasons of ...
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How to find the minimum data point that predicts the target class in longitudinal data

I am working on medical data where a screening is done regularly for 200 days. I need to know the minimum number of screenings that can predict the outcome. I also need to know the best time/times to ...
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Bad metrics results by strong class imbalance in Credit card classification

Hi i'm currently in the process of writing my bachelor's thesis and stuck at a some steps. I've developed a few ML-Model (XGBoost, (Balanced) Random Forest, ElasticNet,...) on an extreme imbalanced ...
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Tile color, shape, and type detection altogether

I'm trying to apply some detections/classification on the set of tiles we have. Specifically, I need to detect color (15 classes), pattern (25 classes- on the surface of tiles, there can be certain ...
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Difference in the value of evaluation-metric in xgb.train() and predict in R

I have trained a xgboost classifier with a custom metric (f1_xgb), that is, the F1 score. Here the important aspect is that I evaluated the classifier on the test set by setting: ...
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Is using Probability Classification to predict whether a restaurant will purchase the best approach?

I have a data set that contains data about restaurants in the United states including menu, foot traffic, type of cuisine, type of restaurant, and other restaurant attributes. I also have a small ...
erich's user avatar
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Unsupervised learning with bags of words with a word metric

I would like to perform clustering on a collection of documents with the assumption that I have a metric $\rho$ which tells me how close two words are to being synonyms. If $\mathcal{W}$ is our ...
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If a set of random vectors are independent then would the join event of the random vector from the set and another random variable independent?

If all x_i from i=1 to n are independent. And y_i is dependent on x_i. Then can we always say that all (x_i, y_i) tuples are always independent of each other? x_i is a random vector of shape mx1, y_i ...
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Relationship among different classifiers of a model in multiclass problems

Suppose we are fitting a LogisticRegression model with scikit-learn, or the same model with pytorch. In multiclass problems, the strategy OneVsRest will fit a different classifier for each of the ...
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Choosing a cluster validation measure for graph clustering algorithm

I am currently solving a clustering problem. Objects to be clustered are represented as sparse vectors in R^N, N=10. The number of objects is about 1kk. To cluster, I build a graph keeping the largest ...
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How to specify and interpret control variables in the model?

I'd like to build a classification model on customers across different countries, but not sure how to interpret the coefficient of those countries and other features, especially features that could be ...
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What feature selection method is ideal for a large dimensional data frame after the result of one hot encoding?

I am trying to solve a sports related multi class classification problem in Python, I aim to train a custom neural network and also a SVM. I have performed prior data cleaning and encoded my data ...
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Confusion Matrix exercise

everyone. While studying and working on some exercises, I found myself feeling lost and unsure about how to solve this particular problem. I'm struggling to identify the True Positives (TP), True ...
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predict if news article belong to specific category or not?

I am still new to machine learning. I am trying to build an ML model to predict if an article belongs to a category or not. for example, I have three categories : [war, politics, and crime]. I choose ...
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Recommendation system NLP ideas

The problem: If we have a clustering problem with lets say x groups. And each group has a document describing it, lets say 3 pages. Then we have n observations each with a smaller piece of text ...
Dylan Dijk's user avatar
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Where can I get 5000+ classified images of zoo animals? [closed]

please help! We are college students doing this for a project. The project is using neural networks and want to build a model that takes in an input of a colored image of an animal and outputs the ...
user90061's user avatar
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Why does data science see class imbalance as a problem for supervised learning when statistics does not?

Why does data science see class imbalance as a problem in supervised learning when statistics says it is not? Data science seems to seem class imbalance as problematic and needing special techniques ...
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Training Loss for Classification Model Isn't Decreasing

I'm currently building a video classification model for engagement detection but I'm having some trouble training it. The model takes in two tensors as inputs: a 10x48x48x1 tensor which holds a stack ...
snowball's user avatar
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PR AUC curve with drop in precision

I have this PR AUC plot, with both PCA and autoencoder related curves having a huge drop of precision in the beginning and then increasing again, with PCA hitting 0 as you can see in the zoomed in ...
GabrielPast's user avatar
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ROC curve for a perfect model, why is AUC 1.0?

According to this article, The ROC curve for a perfect model would go straight up the TPR axis on the left and then across the FPR axis at the top. Since the plot area for the curve measures 1x1, the ...
T. Webster's user avatar
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Ideas on building models to predict the likelihood of prospects converting (making their first purchase)

context: I have a task to identify the prospects who have high or medium likelihood of making their first purchase after they signed up for 30 days, so that our marketing teams can take actions for ...
Iris's user avatar
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Academic name of dataset preparation method with hierarchical-learned labels? - E.g., cold→half-cooked→cooked

What's the name of the dataset preparation method indicating hierarchical ontologies? Assume photos of cold, half-cooked, and fully-cooked chickens. Annotate with temperature data. E.g., at current ...
Samuel Marks's user avatar
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Empty Confusion Matrix and Zero Precision/F-score

Could you please say why I'm getting this warning while doing a binary classification using Artificial Neural Networks? The data are colored images. ...
Totoro's user avatar
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How can I identify coverage types in NFL games using Computer vision

I am currently working on a project that classifies coverage types from sports highlights using advanced computer vision techniques. Next Gen Stats effectively utilizes tracking data to identify ...
Shah Zeb's user avatar
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how many samples do i need to be sure about my model metrics?

i have 50 features(columns) and 100 samples(rows) dataset for binary classification problem, i have build a ML model by using cross validation and it has model metrics like roc_auc=0.71 f1=0.75 ...
M.SEL's user avatar
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how to give numeric value for a categorical feature instances

i have a data set with day of the week. i want to transform this to numerical in the data preprocessing stage. how can i do this? I want to do this in Orange data mining software...thank you
Jerry Campbell's user avatar
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Why is my genetic algorithm overfitting so much?

I'm only training on a fraction of the data each generation: ...
BigMistake's user avatar
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Two-part ML classification model on panel data - is it viable?

I have a dataset of medical encounters, and I aim to predict whether a patient will return to the hospital within 30 days after being discharged. Each row in my dataset corresponds to a specific ...
Frederico Portela's user avatar
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How to impute and aggregate data with ID variant variables for predictive modeling?

I have a dataset that looks like so ID var_id_invariant_1 ... var_id_invariant_p var_id_variant_1 ... var_id_variant_k target 315 25 ... a 2.4 ... A 1 246 31 ... nan 5.7 ... B 0 315 25 ... a 9.4 .....
Mateusz's user avatar
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How to deal with categorical disalignment in test and train in binary classification problems

I have a train and test datasets (600k observations) that have different categories for the same categorical variable. For example train has the categorical variable Letters having unique categories ...
kyara's user avatar
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Why is cross-entropy increasing with accuracy?

I'm making an implementation of the softmax regression and I'm struggling to understand the nature behind the problem of increasing value of Cross-Entropy: $H(y_i, p_i)=-\sum_{i=1}^C y_i log(p_i)$, ...
JoshJohnson's user avatar
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Car Make and Model detection

I am trying to develop a deep learning model that given an image of a car, it detects a car's make and model among 50 different brands, each with say another 50 models. What approach is probably the ...
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Seeking datasets for training a Language Model on U.S. mortgage loan processes

I'm in the process of training a Language Model (LLM) and require datasets that encompass various aspects of the U.S. mortgage loan process. The model's aim is to understand and simulate decision-...
Anand 's user avatar
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1 answer
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How does oversampling or undersampling approch is going to help during the testing on real time data?

We have a dataset with class A as 10% only and Class B as 90% . Let say we did undersampling or oversampling on training data and we made 50% of class A and 50% of class B. But in reality the data ...
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