Questions tagged [classification]

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

Filter by
Sorted by
Tagged with
1
vote
0answers
6 views

Specifying class or sample weights in Keras for one-hot encoded labels in a TF Dataset

I am trying to train an image classifier on an unbalanced training set. In order to cope with the class imbalance, I want either to weight the classes or the individual samples. Weighting the classes ...
0
votes
2answers
17 views

Best Python NLP library for supervised topic classification

I have a labeled dataset that I have ingested into a dataframe. It consists of news articles, ...
0
votes
1answer
24 views

CNN for image classification with two outputs

Is it possible to classify my images (cars parts) by the type of cars part(door, window ...) and also by the view of the image( front, back, right, left, top and bottom). My pictures are labelled like ...
0
votes
0answers
7 views

Can ReliefF implicitly predict non-linear correlation between features and targets?

Let's assume that we have a collection of instances with their features and already labelled and train them for Relief/ReliefF classifier. If the targets themselves have parameters that defined ...
-3
votes
0answers
21 views

which machine learning algorithm would give high accuracy in predicting the movie rating [closed]

I want to predict the movie rating with the help of voted users, profit, FB likes, etc. which algorithm would the best to predict it
1
vote
1answer
29 views

Explanation of random forest performance difference to when using categories and when using dummy variables

I have some hand coded feature which is a category with values "High", "Low", and "Normal". I created this feature myself and my problem performance (classification) ...
0
votes
2answers
31 views

Is it recommended to compute the average of metrics for classification?

For computing the performance metrics of the models used for classification. Is it recommended to repeat the experiments many times (for example 10 times) and compute the average? In my case, I used ...
0
votes
1answer
15 views

Subsampling the “right” amout of data to train an ML model

I am training a machine learning model (i.e., a classifier) on a large dataset. I know that I can get the same results using less data (about 30%) but I would like to avoid the trial and error process ...
0
votes
1answer
12 views

How to interpret classification output - Predective model

What is the significance of macro avg ? I'm not sure if this report signify a good predictions by the model. Thanks in advance.
0
votes
0answers
24 views

How to Classify Game Stages Based on Bitrate Time Series Data

I need suggestions for my project and would be glad if you would give me a hand. I have a dataset of frames obtained from the old-school game DOOM. Each frame in the dataset has the following columns: ...
0
votes
1answer
12 views

Evaluating model with categorical target variables

I converted all the numeric target variables of MNIST dataset into categorical variables. So, 0 became zero, and so on. Next, I ...
0
votes
0answers
16 views

What feature selection technique would you recommend for selecting many features (in the thousands)?

I have a data set that has a large number of features (~8k features) and I want to limit the number of features so my model does not overfit but performs relatively well. I have mix of categorical and ...
1
vote
1answer
17 views

How do you perform multilabel classification that is also a multiclass problem?

I have a data set in which each row of data belongs to certain classes/labels. text class1 class2 class3 text1 pos neg na text2 na neg na text3 na neu na text4 pos neg neg text5 neg neg na ...
1
vote
3answers
44 views

Building a multiclass classifier that can handle classes it has never seen?

I am given a dataset that has free-form text and a category associated with it. There are 100 different categories and 3000 records for each category. The goal is build a multiclass classification ...
0
votes
1answer
17 views

Addressing polysemy in NLP tasks

Looking for modern algorithms using NN Language Model implementations addressing polysemy in NLP tasks, including text classification, question answering and topic modeling. Transfer/Zero-short ...
0
votes
0answers
19 views

Margin of error for imbalanced discrete set

I'm evaluating the performance of a classifier regarding its false negatives. The classifier performed over 9090 samples, from which 9000 were labeled as negative. I randomly chose 800 samples (out of ...
0
votes
0answers
8 views

Difference between MAP@K for recommendations, MAP from Precision Recall Curves and Macro-Precision

I have been using the 3 metrics independently for a while now, but trying to figure out if they are actually 3 separate things (with similar-looking definitions/names) or there is some underlying ...
1
vote
1answer
29 views

How to select the split point for Continuous Attribute Age

For the above table, midpoints for possible split points are 22.5 and 35. I have calculated the entropy and gain for each value and 35 had the minimum Entropy and highest gain. Is it correct ? Given ...
-2
votes
0answers
26 views

Implementing a confusion matrix for a CNN model

I have created a convolutional neural network model which classifies malware based on the Malimg dataset. Below is the model and the results from the first run: ...
-1
votes
0answers
27 views

Dividing dataset into Training, validation and test set [duplicate]

I have a dataset of 535 classes (258 194 images) and I want to divide it into train, validation and test set. I am a new learner in image classification with CNN, should I do that manually or is there ...
0
votes
0answers
11 views

Classification based on color clustering

I need to classify some domain specific images by analysing their color distribution. I have annotated data; this last classification step is supervised. After some preprocessing and masking and other ...
0
votes
1answer
45 views

How to have Multiple labels in a single video?

I am building a Tennis stroke classification system using CNN. I assume each stroke contains 3 steps/classes ('Ready', 'Impact', 'Finish'). I want to train a model which will predict whether the input ...
0
votes
1answer
19 views

how to do regression and classification in a same time?

I was thinking of doing a job including regression firstly, then doing the classification. I read lots of sources that are saying it is Semi-Supervised learning ...
0
votes
0answers
18 views

Theoretical question around multiclass classification

Assume there's a customer dataset with monthly installments repaying goods purchased in advance. The objective is to build a model predicting who is going to be bad debtors and who can afford to buy ...
0
votes
0answers
56 views

Testing accuracy very low, while training and validation accuracy ~ 85%

I have a training dataset of 10000 pictures and a test dataset of 15000 pictures. There are 23 types of birds. First of all, I imported the necessary ...
0
votes
0answers
19 views

How can I prevent overfitting?

hope to find you well ! I am trying to build a model to classiffy customers with propensity to buy, but i cannot get rid of overfitting! My approach is the following: I have created the train dataset ...
1
vote
2answers
30 views

Do larger numbers of hidden layers have a bigger effect on a classification model's accuarcy?

I trained different classification models using Keras with different numbers of hidden layers and the same number of neurons in each layer. What I found was the accuracy of the models decreased as the ...
0
votes
0answers
15 views

Classification of text without punctuation [closed]

What methods exist to classify text without punctuation? Any traditional methods and/or deep learning algorithms with transfer / zero learning out there?
0
votes
0answers
6 views

Error in discretizeDF.supervised(formula, data, method = disc.method) :data needs to be a data.frame

I am using arulesCBA on dataset of words with class attribute which is polarity to be positive or negative. First, I am converting the words to numeric values by using ...
0
votes
0answers
17 views

Handling Null values

I am trying to fit a RandomForest model for a binary classification dataset and I have some feature like, the sales for a particular store and yes/no information ...
0
votes
0answers
25 views

Can one still train a classifier with an unbalanced data set?

I want to train a binary Naive Bayes classifier. The problem is, is that I have an unbalanced set at my disposal, where the ration between the two classes is roughly 2:1 (250 examples from the first ...
0
votes
0answers
17 views

CNN seems doing good during training and validation but not really

I'm doing a simple binary classification using this dataset ...
0
votes
1answer
32 views

High Recall but too low Precision result in imbalanced data

I was training a model using XGBoost Classifier on heavy imbalanced data base with 232:1 of binary class. Because my training data contains 750k rows and 320 features (after doing many feature ...
1
vote
2answers
19 views

Word list as a baseline for measuring a classifier's performance?

I am working on a simple Naive Bayes classifier that categorizes text messages as either "positive" or "negative". I was told that the simplest baseline to measure the classifier's ...
0
votes
0answers
8 views

Model performance in different snapshots varying

I am trying to solve this problem. A medical representative needs to visit some doctors' clinics and for that a model will generate probability scores for visiting a clinic. I ma using a tree based ...
1
vote
0answers
32 views

VC-Dimension of Axis Aligned Right-Angle Triangles and 5-points Convex Hull

I am having trouble proving the following fact about VC dimension of triangles. Consider right-angle triangles in the plane, with the the right-angle in the lower left corner. The hypothesis in our ...
0
votes
1answer
8 views

Chossing between gradient boosting algorithms

I just stepped in machine learning competitions and it looks like most of the mid-sized dataset competitions are won by Gradient boosting based models. However I came accross case where LightGBM,...
1
vote
2answers
16 views

How to properly use oversampling without inflating results?

I am using with a tiny private dataset (over 192 samples) with 4 classes. A preprocessing step is trivial in order to do any classification. Among feature selection and extraction techniques, i ...
0
votes
1answer
11 views

Encode the days of week as numeric variable

I would like to understand if there is the possibility to encode the days of the week as a single numerical column to preserve the ordinal relationship between the days. My task is a classification ...
0
votes
2answers
29 views

In classification task, is it possible that a truly classified data has a higher loss compared to a miscallisfied data?

Given a classifier using softmax, is it possible that say, for data point a which our model has correctly classified, has higher loss compared to data point ...
0
votes
0answers
15 views

Predicting in decision rules

Sequential covering is a type of decision rule procedure that repeatedly learns a single rule to create a decision list (or set) that covers the entire dataset rule by rule. Given a training dataset, ...
0
votes
1answer
13 views

Custom thresholds on categorical classification

When assessing a binary classification task, it is possible to search for particular threshold in order to have better score on some metrics (f1,recall,etc) through numerous methods. Unfortunately, it ...
0
votes
1answer
34 views

Training loss = 0, training accuracy =1, validation and test around 85%

I have created different CNNs for doing image classification. The dataset is this: https://www.kaggle.com/crowww/a-large-scale-fish-dataset There are 9 classes, and each class contains 1000 images of ...
0
votes
1answer
29 views

Why my classification accuracy is high for both training and testing data?

I have a dataset with 10 features and 1 binary classification target. I tested this dataset with decision tree classifier. I did some basic check like missing values but the data looks clean. My ...
0
votes
0answers
9 views

Oversampling Using the Orange Data Sampler Widget

It was pointed out in the help section of the Data Sampler widget that it could be used for under or oversampling. I used the Attrition dataset where the class imbalance is 1233/237. I separated the ...
5
votes
1answer
55 views

Suitable metric choice for imbalanced multi-class dataset (classes have equal importance)

What type of metrics I should use to evaluate my classification models, given that I have two imbalanced multi-class datasets (21 and 16 classes, respectively) where all classes have equal importance? ...
1
vote
1answer
113 views

How to use SMOTE in Stacking in SKLearn?

I have a data set X,y and split them to train and test data. ...
1
vote
1answer
22 views

Changing behaviour of an ML model

I am trying to create a ranking system for recommending books to an user. Let's suppose we have some subjects of books like 'A', 'B', 'C', 'D' and from the past behaviour, it is observed that the user ...
1
vote
0answers
25 views

When should you use deterministic classification rather than probabilistic

Probabilistic classifiers look really good because they give you more information than deterministic ones i.e. estimated probabilities of class memberships rather than just which class the model ...
0
votes
1answer
18 views

Understanding PyTorch's BCE Notation

According to the PyTorch documentation for the Binary Cross Entropy Loss, we can write it as follows: $$l_{n} = -w_{n}\cdot \left[y_{n}\cdot \log \left(x_{n}\right) + \left( 1-y_{n}\right)\cdot \log\...

1
2 3 4 5
52