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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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Using classifier's probabilities as independent variables to predict Y

Suppose you have a classification task y~X with (n_samples,m_features). A colleague told me that it is correct to run r different classifiers to predict y based on X and then use the probabilities ...
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1answer
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Find best machine learning for predicting category of products

I have a dataframe that contains product and in this dataframe I have some features like: brand, cat1, cat2, ...
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In votingclassifier, why does soft voting gets higher accuracy score than hard voting? [on hold]

In all my runs, i saw that hard voting gave a lower accuracy than soft voting, is there a reason behind this?
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23 views

Multi-class classification dataset structure

I have a question regarding how to setup a dataset for modeling. Let’s say I have a dataset representing which car a person will buy depending on some characteristics: The dependent variables would ...
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2answers
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Does a precision score increasing with a higher number of folds mean the model will improve with more data?

I have been working on a pretty simple text classifying module (tfidf + Random Forest). My manager insisted on using a simple .7/.3 split rather than doing cross validation, then was adamant about ...
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1answer
12 views

Are there known techniques to transform features X classified as C to features Y classified as C'

I don't think the wording of my question is that clear myself, but I don't have any better words suitable for a title (on top of my head at least). I was wondering if given features X that is ...
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Keras: Poor classification by copying model weights before fine tuning

I have a pretrained LSTM model, A. After fine tuning the model (A) on my data for 2 epochs, I get number of incorrect classifications as 46. In the second scenario, before fine tuning the model A on ...
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25 views
+50

Classify big changes in target variable

I am using a CNN to predict large changes in my target variable X. I am classifying several "set-up" states visually from my images. I am only interested in big changes, or maybe no change. So, I can ...
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How to optimize function built on top of the classifier?

I have a dataset with classification model build for it for $n$ classes as target. And also using the probabilities for each class, which classificator returns, I built confidence function for each ...
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1answer
41 views

How to extract and classify data from a column in excel?

I have a column in an Excel sheet that contains a lot of data separated by || delimiters. The data can be classified to some classes like Entity, IFSC codes, ...
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19 views

Word classification in the context

I'm trying to solve a 'negation-like' classification problem, where I need to classify whether a certain word within the context has negative or positive label. For example, how to identify whether a ...
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Sci-Kit Learn Neural Network Attribute Advice

I'm working on a neural network for a set of weather data, and I'm looking for advice on what attributes should be included, and which are unnecessary. The data I'm working with includes 16,000 ...
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Why is recall so high?

I've built a binary classification model based on Keras and I am getting about 70% accuracy, and about 72% precision and 88% recall, making up to 79% F1-Score. I've tried different data models (...
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Least Squares optimization

The cost function given as $\hat{\beta} = (Y - \beta X)^T (Y-\beta X)$ is used to evaluate the weights $\beta$. Here $X$ is the data and $Y$ is the output. On taking the derivative, we get the ...
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Assessing performance of an agent based on commission rate, market share and revenue

I have a set of data for agents selling properties (apartments) for a company in different states. The company would like to assess the performance of the different agents given the following: Number ...
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1answer
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How should multiclass classifier performance be measured when one type of error is preferred over another?

Sorry if this question has been asked before--I am having trouble searching this topic since I'm not sure of my wording. Say you have a classification problem where there are more than two labels ...
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1answer
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Document parsing modeling and approach?

I'm relatively new to data science / machine learning (yes, I know) and am experimenting with text analysis. I only want a relatively naive approach and am looking to know whether my approach is valid ...
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what is fuzzy svm?

I have to solve this question for my homework but I don't get how to formulate svm to FSVM. can someone please guide me? What is your idea to have a model of SVM classifier in which instances can ...
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Why am I getting such a low precision after performing oversampling and undersampling?

I am performing fraud analysis on credit card fraud committed dataset. I am performing oversampling by .sample(oversampled_class_size) and undersampling by .sample(undersampled_class_size). I am ...
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3answers
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How to get accuracy, F1, precision and recall, for a keras model?

I want to compute the precision, recall and F1-score for my binary KerasClassifier model, but don't find any solution. Here's my actual code: ...
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1answer
24 views

Mathematic explanation needed for a univariate classification method based on solving a quadratic equation

I read a piece of codes on classifying image hue values into three classes with derived thresholds. The thresholds are calculated by simply using a quadratic formula. The related documentations for ...
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Implementation of Siamese network

What would be the ideal ratio of positive, negative image pairs, and the number of image pairs to classify if two images are of same person in Siamese network ?
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1answer
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What is difference between leave one subject out and leave one out cross validation

What is the difference between leave one subject out cv and leave one out cross validation (loocv)? are they same or different?. I have images of 24 subject and according to literature, leave one ...
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2answers
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Time of trainig vs time of prediction, which one is used during classification algorithms comparison?

I need to use many algorithms for making a binary classification, such as Logistic regression, SVM, XGBoost, CatBoost, ... I get an interesting improvement but All of those algorithms (except LR) take ...
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3answers
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when can xgboost or catboost be better then Logistic regression?

I need to improve the prediction result of an algorithm that is already programmed based on logistic regression ( for binary classification). I tried to use XGBoost and CatBoost (with default ...
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Activity Classification using accelerometer data?

With general machine learning classification algorithm we can easily classify the activity a human is doing by training accelerometer data. Will it be possible to find the quality of his activity. [...
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1answer
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How reliable are model performance reportings?

I had a conceptual doubt about estimating and reporting a classification model's performance. Say my model works with range of depth values and gives out different readings of test errors. We choose ...
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2answers
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Classification model for recommender system?

I have some data for various customers choosing one of 'n' products or no product. I have some useful features for each customer. I can build a multi-class classification problem out of this data and ...
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Problems successfuly implementing stacked autoencoder in binary classification problem

Hi im currently working on a binary classification problem, currently i haven't had much success with it however. From the paper A https://journals.plos.org/plosone/article?id=10.1371/journal.pone....
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1answer
33 views

Why doesn't class weight resolve the imbalanced classification problem?

I know that in imbalanced classification, the classifier tends to predict all the test labels as larger class label, but if we use class weight in loss function, it would be reasonable to expect the ...
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Word classification (not text classification) using NLP [closed]

I have been trying to extract Person name and Company name out of string. But, I have been facing lot of difficulties. I have a dataset of names and a dataset of company names. In the string, I wish ...
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1answer
29 views

classification on very small dataset

I have a dataset that consists of 365 record, and I want to apply a classification model on it (binary classification). As an output, in addition to the classification labels, I want to retrieve as ...
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I have created a model that classification sentences. How do I create a good dataset when I train this model further?

I used bidirectional lstm I have a model that classification as spam and general trained with about 130,000 data. The model has 90% accuracy for sentences over a certain length, but 75% accuracy for ...
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How to solve a classification problem when the independent variables/covariates/feature vectors form a time series?

Cross posted here: https://stats.stackexchange.com/questions/389189/how-to-solve-a-classification-problem-when-the-independent-variables-covariates, but no answer; hence trying here as well! I hope ...
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1answer
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Desicision tree classification with a “false” attribute

This is a pretty specific problem but I think it can help me understand better the whole concept of the subject. A doctor in the hospital is in charge of 20 medical students. For every patient, the ...
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Online service for crowdsource text labbling [closed]

I'm trying to make a text classificator for short texts. For that task, I need a labeled samples dataset. I already have samples but most of them are not labeled. I'm tired to label them in excel ...
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ctc forward backward algorithm - why is it being used?

as per ftp://ftp.idsia.ch/pub/juergen/icml2006.pdf fwd bw algo helps us speed up discovery of the happy path. For e.g. if the GT label is DOG and we have 10 time steps , the possible label sequences ...
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How to balance specificity and sensitivity?

I have included accuracy and feature minimization in my fitness function. How should I balance specificity and sensitivity?
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Classification: how to handle reviews/long english words in feature set with all other numerical features

I am currently working on an use case where feature set contains numeric values such as amount, as well as a review feature which contains long winded english text. the english text will very well ...
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How to perform T-test and chi square test to my categorical variables like country, education and predict accuracy using logistic regression?

I'm new to Data science. I have been working on a classification project which has columns (Sex, Age, Occupation, Marital Status, education, country, relationship,capital gain, income). Here income('&...
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9 views

Text segmentation based on most probable classes

I am working on a text classification problem. As training data, I have human annotated text, which was manually segmented into sections and then these sections are labeled with some class. Training ...
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1answer
29 views

Purpose of test data in binary classification

I have a highly biased training dataset where AppId 6,7,8,9,10 are almost never purchased. I made this up just to see how good my comprehension of calculating the classification metrics is such as <...
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1answer
68 views

How to calculate Accuracy, Precision, Recall and F1 score based on predict_proba matrix?

I found this link that defines Accuracy, Precision, Recall and ...
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1answer
13 views

Product classification in hierarchical categories based on multiple parameters and non-standard descriptions

I want to start a machine learning project in my company and a really big pain for spend analysts is to classify the products that buyers order for maintenance, tooling, raw material and such, as the ...
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2answers
41 views

What could explain a much higher F1 score in comparision to accuracy score?

I am building a binary classifier, which classifies numerical data, using Keras. I have 6992 datapoints in my dataset. Test set is 30% of the data. And validation set is 30% of the training set. ...
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1answer
19 views

Data splitting for a binary classification model

I'm trying to build a binary classification model that will tell who's going to buy the product and who's not. I've heard that splitting a dataset into two different subsets is a common way when you ...
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0answers
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Doc2Vec for dataset with several text fields: concatenate or separate models?

I have a dataset with several fields: description, name, header. I want to train doc2vec out of it, so that I could use vectors for classification. So I wonder, ...
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2answers
66 views

How can I check if a bigger training data set would improve my accuracy of my scikit classifier?

How can I check if a bigger training data set would improve my accuracy of my scikit classifier, is there a method or something?
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1answer
53 views

CNN to many outputs

I have a dataset with 100 columns (categorial one-hot encoded) and 1 column with text data (simple sentences) and i want to build a neural network to arround 380.000 outputs labels. I have no idea ...
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State of the art PHP malware classification

PHP malware classification's features can be seen from different angles: entropy analysis, frequency analysis (1) opcodes parsing (using CNN and LSTM architectures) compiling PHP to binary and ...