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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Is there a way to assess how much and in which direction a predictor is associated with class in my classifier?

I searched the forum, and couldn't find a matching question. I am building an MLP to predict an outcome (occurrence of a medical condition) in Weka. Previously I identified positive and negative ...
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What does $w_{ni}$ mean in the weighted nearest neighbour classifier?

Wiki gives this definition of KNN In pattern recognition, the k-nearest neighbors algorithm (k-NN) is a non-parametric method used for classification and regression. In both cases, the input ...
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How can I build a single multi-class GBM model where classes are related and may add noise in one vs all approach

I am trying to build a multi-class GBM model where classes are let's say 0,1,2,3,4. These classes are related in a way that while predicting any non zero class I would want to eliminate classes before ...
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How to build a data labelling tool?

I want to classify strings of text data using a supervised machine learning model, but unfortunately I do not have access to the class labels of my data (they don't exist). Rather than outsource the ...
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Peeking Inside the Black Box, can Feature importance indicate overfit?

my basic question is: can permutation feature importance be used to identify overfitting? when you have a binary classifcation problem with balanced classes (i.e. 70 x yes, 70 x no), when none of the ...
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What's the meaning of building classifiers for each class in binary classification?

The question arises when I'm using DistributedRandomForest from the H2O package and find the ...
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improving performance of KNN classifier on FFT

I need to classify whether a product is passing or failing based on a noise check. I have 100 labeled "good" product and 100 "bad" product. For each, I recorded the sound for 3 seconds and each chunk ...
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20 views

Probability of occurrence based on historical data of occurences [on hold]

The dataset is of occurrence of particular insects in a location for the given year and month. This is available for about 30 years. Now when I give a random location and year, month of future, I want ...
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CatBoostClassifier - hyper parameter tuning results are unexpected [on hold]

CatBoost version 0.16.4 NumPy version 1.16.2 Pandas version 0.24.2 Hyperopt version 0.2 ...
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Provide a perceptron learning procedure from the initial separating line linearly separating the classes [on hold]

I try to understand how to solve this type pf questions. I have the following input x and the labels. $Points$ $Label$ $(0,0)$ $1$ $(1,0)$ $1$ $(0,1)$ $1$ $(2,2)$ $-1$ $(3,3)$ $-...
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Using k-means to segment customers in the positive class

I have some labeled data (0=didn’t cancel, 1=canceled) that I am creating a model for in my marketing class. On top of predicting who is likely to cancel, I’d like to explore the possibility of ...
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group in group lasso [on hold]

How to make group in group lasso for classification task? I have a data matrix for 20530 and 220 observations. I just wonder how to define group index for in this code. ...
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Cross-entropy loss when some categories are broader than others

Let's say I want to write a classifier for pictures of dogs. Most importantly, I want to know whether something is a picture of a dog or not. Secondarily, it'd be nice to know what breed the dog is. ...
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How to find correlation if we have continuous and categorical variables present in my dataset as features and target is again binary

I am working on classification problem where I have categorical and continuous features however the target is binary. What is the best way to check correlation with respect to target variable. Also I ...
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how does class 0 scores in the classification report are calculated ( sklearn python )?

Here how these class-0 probability are calculated?? print(classification_report(y_true, y_pred, target_names=target_names)) precision recall f1-score support ...
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multiple hypothesis tests for features selection (classification)

I am wondering whether running multiple hypothesis tests (t-test / Mann Whitney) as a first step in classification problem. Specifically: given a data set with k features (k=3 in the example bellow),...
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SVM: achieving ROC curve by varying misclassification costs

Assume that we have SVM model for binary classification with objective function as follows: $$ min(\frac{1}{2}\omega\cdot\omega +C^{+}\sum_{i|y_{i}=+1}^{n}\xi_{i}\quad+C^{-}\sum_{i|y_{i}=-1}^{n}\xi_{i}...
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Cohen's Kappa (observer variability) with partially ordered sets

I was wondering if there is a common way to compute Cohen's k when the values are partially ordered sets (of a lattice). My data roughly looks like the table below. There is a default lower bound (...
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Tune hyper parameters using cross validation

I have around 228 samples and 100 features in total. I wanted to do some stability analysis on the data, so I did repeated 10-fold cross validation on the entire dataset and obtained the mean ...
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1answer
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Multiple Imputation by Chained Equations (MICE) Explained

I have seen Multiple Imputation by Chained Equations (MICE) used as a missing data handling method - is anyone able to provide a simple explanation of how MICE works?
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Classification Model - How to Preprocess Text

I have a Dataframe that contains 2 columns: 'Skills' column - each cell contains a list of strings describing different technical and soft skills of a person, e.g: [Python,SQL,Java,Team Management,...
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Decision boundary for categorical Bayesian network

I know that categorical Naive Bayes (categorical predictors, binary target) has a linear classification boundary. I'm wondering what the decision boundary for an arbitrary categorical Bayesian network ...
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Can we use SVM and Random forest for classification of one-dimensional data?

I am working on flood inundation mapping using remote sensing data. I am using a single band, a simple threshold value can be used to separate land and water. I am interested in knowing, can we use ...
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Creating a classification model for a target value with Poisson distribution

I have a dataset with a target variable following Poisson distribution. It starts at 0 and goes until 30. But there are 8300 0's and only 2 30's. From this data, I need to create a classification ...
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Does a lot of classes returns a better accuracy?

I have a supervised images classification problem, I am using Convolutional neural network model to solve it. there is 8 classes: what can be result in good accuracy to train the model on all the 8 ...
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What is the effective difference between PCA/SVD feature selection as input to logistic regression and Lasso regularization? [duplicate]

I have a problem with where the number of features (around 10k) is almost of the same order as the number of records in my data (around 100k). I'm using this data in a supervised classification task ...
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How to build a propensity model when you have only one target class?

I have a use case in which I am trying to build a model which predicts most likely customer to invest in commodity (Share market data). My dataset consists of customers who invest in commodity ...
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Regression to Classification and back to Regression

Is it reasonable to transform regression problem into classification by binning target variable into classes and construct regression curve separately on each class?\ Precisely, if my goal is to ...
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High test AUC and good lift chart from a randomly generated prediction?

For a binary classification problem, is it possible to still have test high AUC (~0.9) and good-looking lift chart if the model learned nothing but random noise?
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Evaluating a model with Log Loss

I have been looking at alternative ways to intuitively understand the "goodness" of probability predictions from 2-class logistic regression models (and other ML classification models) and came ...
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Binary classification of individual microcalcifications (micros) in breasts when there are multiple micro's per patient and only one label per patient

A micro(calcification) is something which can be found in a breast through a mammography. A breast can contain multiple micros. Some micros are harmless (benign), some are associated with cancer (...
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intuition behind classification model confidence intervals

What do confidence intervals mean in classification problems? I recently did a study with glmnet in R, and got this confusion matrix : ...
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22 views

SVM classification reliability with little data

I'm trying to train an (RBF) SVM model to get a binary classification (1 = class, 0 = no class) based on some features. My dataset is quite small: I have 2500 records for training and 300 for tests. ...
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How do I deal with large amout missing values in a data set without dropping them?

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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Feature selection for classes with only a sample

The title doesn't make sense but allow me to explain. I have a set of gene expression data with over 10000 genes as features. There are roughly 30 samples, and let's say there are 10 from class A, 10 ...
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How to do transfer learning with limited data

This is my first question here, please be gentle with me. I'm working on point cloud classification problem. I'm building a NN to classify point cloud. I found a really nice architecture that I want ...
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Normalizing data in classification [duplicate]

i am following a classification tutorial and i encountered this line of code and i dont understand it . it says that we are going to normalize our data. anyone with knowledge please explain ...
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Using KNN for audio classification based on FFT

I need to classify whether a product sound "good" and "bad" based on FFT of its audio recording. The FFT magnitudes are show for frequencies from 0 to 7khz, with a frequency resolution of 5 hz, so ...
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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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Link between classification scores and probabilities?

I am aware that classifiers are not necessarily calibrated in probability (see: scikit-learn manual here). I wanted to know more about what we can say about the link between scores and probabilities. ...
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Best model for multiclass classification

I have a dataset which consists of categorical predictors, and I hope I can classify them into 3 different classes. Instead of creating a "Black box" model, such as neural network and svm, I would ...
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Multi-step ahead binary classification of multiple multivariate short time series

I'm working on a project where I need to identify loan defaults. I have around 50 000 time series, each time series represents a loan and is composed by few time steps (from 3 to 18). Each time step ...
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Optimal Threshold On Single Input

Suppose we have a sensor that measures "how red" an object is. Using this single input, we would like to classify whether or not the object is round. We have a data set comprised of tuples where the ...
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3answers
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Machine Learning - How to Sample Test and Training Data for Rare Events

Suppose I have a data set with 1000 observations. I want to train and test a Classification Model to predict a target variable as true or false. However, in my observation set, true occurs only say 10%...
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Hierarchical Text classification

I am working on a project with a huge number of big groups of sentences! I need to classify each sentence based on the sentence and other sentences on the group. Actually there is 2 level of ...
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1answer
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Can I use balanced subsample for training and imbalanced for testing?

I am working on classification problem and I have highly imbalanced, but huge data set (I have more than 2mio samples). Now my question is: If I choose subsample of only 15% of the data for training, ...
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Comparison of classification accuracy with permutation tests [closed]

My dataset contains 4 balanced classes (A, B, C and D). By carrying out two independent binary classifications, I want to compare the classification accuracy of (A vs. B) with that of (C vs. D). ...
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scikit-learn feature selection on k-fold loop

I am using the iterator of StratifiedKFold from sklearn and i've noticed that i must include a process of feature selection on ...
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Multi-output and multi-class classification?

I have a question regarding the following classification task. I guess that the forecasting problem can be seen as a multi-output and multi-class classification problem. But i am absolutly not sure. ...
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Validation Set Accuracy Significantly Higher than Test Set

I'm building a binary classifier, where each record is a task, and the response variable is whether it was completed on time. I have data spanning several years, with features regarding complexity, ...