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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8 views

Transfer learning from emotion to fatigue EEG

I have trained a CNN model on multi-emotion EEG data, and I want to classify fatigue EEG data with this model. Is this task transfer learning or not?
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Derivation of closed-form ROC expression under binormal assumptions

It's a known result that, under binormality assumptions, the area under the ROC curve (AUC) for a binary classifier has the following closed form. Formally, define the class conditional mean and ...
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Getting binary class from continuous values of neural network output [duplicate]

I have a custom neural network that I wrote from scratch and it does lot of mathematical computations and the output is a continuous value. I want to get the binary class output from these continuous ...
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LLE and ISOMAP, strange question and intrinsic low dimensional structure?

I prepare for PhD entrance exam on AI and one question is surprized me. which of the following techniques using intrinsic low-dimensional structure detection for dimension reduction? A) ISOMAP B) ...
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How to choose the correct number of classes? [closed]

I have a dataset of 650 observations and 32 features, where each point is assigned to discrete value from $\{1,2,..,20\}$. The distribution of the labels is described by the below boxplot and roughly ...
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Determine the optimal threshold for sigmoid layer in neural network for binary classification [duplicate]

I have a neural network that gives out a continuous value as output and I need to classify it as class 0 or 1. I am currently using a sigmoid on this continuous output value but after sigmoid the ...
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Loosing performance in a model - calibration? [duplicate]

I am trying to understand what should I do when a models looses performance. Right now, when a model looses performance I am just creating a new model with new data but I’ve heard about the concept of ...
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Why are odd-degreed polynomial kernels slower than those with even degrees for SVM?

I have been using one-class support vector classifiers to extract features for multinomial classification. I noticed that fitting time is much longer when the degree of the polynomial kernel is odd. ...
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Advice on Text analytics : Predict difficulty levels [closed]

This post is hidden. You deleted this post just now. I'm looking for some advice on a classification model I'm working on. I have these two datasets : ...
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How do I calculate the adjusted chance level for a classifier, if the features also affect the chance level?

If I have 5 different classes, and split the data into 70% training and 30% testing making sure each class is represented equally in both. Then I extract features from them in a One Vs. All approach, ...
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Machine Learning Models for Classification with Categorical Variables

To start, I'd like to say I have very little experience in machine learning, or statistics/computer science in general. What I am interested in is a list of models I can use to classify a binary ...
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How to do manual leave one out cross validation using for loop without splitting data into training and test set? [closed]

I would like do leave one out cross validation by creatint a for loop my linear regression classification but I'm getting the misclassification rate as 0 I believe in each loop I'm meant to leave one ...
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p value for Brier score [closed]

Does it make sense to calculate a p-value for the brier score? Does it even exist? I'm doing a logistic regression on classification (0 vs 1) and got the Brier score. How do I know if the brier score ...
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What is meant by relative frequency in calibration curves

After reading docs on scikit learn on the probability calibration there's couple concerns that bug me. I don’t really understand how the curve values are calculated (y-axis) namely the frequencies. ...
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Interpreting NaN values for precision in Confusion Matrix

Please refer to the confusion matrix here: https://imgur.com/a/Iq1epre Would I get precision values of NaN because of 0/0 in the right most columns? Is that even possible? How should I interpret this? ...
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How to predict a class between uneven datasets

I am trying to predict obesity using two datasets. The first (Diet) has 20k values in two columns: Diet [ID, Calories(float)] The second dataset also has two columns: Obesity [ID, Level(1,2,3)] ...
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Should I use every Dicom slice of a Dicom series?

I have a skull fracture CT scan dataset, consisting of fracture or normal cases. My question is: Let's say patient-1 has a skull fracture, and his CT scan has 300 Dicom slices. Now should I label ...
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Binning Calibrated probability scores for business use

Context: We have a model that outputs calibrated probability scores for a binary classification problem (events/nonevents). There is a general business requirement that we bin these outputs further to ...
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1answer
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How to determine which user features are associated with conversion through a funnel?

I have a dataset of user demographics (i.e. region, age, gender etc.) and each step of a conversion funnel that each user reaches (i.e. site visit, placing item in cart, checkout page, purchase). I ...
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1answer
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How to calculate F1, Precision, and Recall for Multi-Label Multi-Classification

I have a predictive model as follows Sample1 Sample2 Sample3 Sample4 Red Yellow Blue Green White Black Orange 65 21 55 40 0 0 1 0 1 0 0 31 40 44 30 0 0 0 0 0 0 0 33 44 56 66 1 0 0 1 0 0 1 63 77 ...
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Explainable AI - Traditional ML algos

In my work, I mostly use traditional algorithms such as Logistic regression, Linear regression, SVM, Naive Bayes, Random Forests, Decision Trees and Boosting etc to analyze data and make predictions. ...
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1answer
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Generative Models - Class Conditional Density and Posterior Probability

In the section 1.5.4 of Bishop's PRML book, a brief description of generative models is given. For classification decisions, it is stated that "the class- conditional densities may contain a lot ...
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Relation between AUROC and threshold

As I understand, AUROC tells us the probability the model will score a randomly chosen positive class higher than a randomly chosen negative class. Meaning that, if AUROC = 0.7, than we expect that ...
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One response variable with multiple categories VS Multiple binary response variables

I'm working on a project and my main dataset consists of approximately 140 independent variables and one response variable with 5 levels/categories. I have an unseen testing dataset and my objective ...
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Relation between the lattice points in ROC plot and different pairs of positive and negative classes

Suppose you have a classification problem and you get the following scores from your hypothesis: \begin{bmatrix} 0.87 & 0.30 & 0.40 & 0.10 & 0.23 & 0.70 & 0.90 & 0.60 \end{...
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AUC with different threshold

I know AUC is supposed to be independent on the threshold, which means AUC does not change while the threshold changes. However, I'm getting different AUC values while changing the thresholds. I'm ...
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Find key nodes in Graph Neural Netwroks

Given a graph dataset, in which links of graphs are the same while features of each node may be varied, how can we locate those critical nodes in this graph structure that contribute the most to ...
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Multivariate logit: evaluate contributions of predictors to estimated probabilities

In a logistic regression with multiple regressors, is there a way to analyze the contribution of the predictors on the dependent variable? (e.g. how would one understand why did the probabilities ...
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Minimizing population risk for logistic loss

I am working on trying to show that the minimizer is equal to as given in this question. However, I can't this exact result and am starting to my book exercise has a typo. Here is my work:
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Imbalanced classification using K-nearest neighbors classifier

For an NLP classification task I need to train two different classifiers and I've chosen to use a RandomForest and KNeighbors both the scikit-learn implementations. My dataset is strongly imbalanced. ...
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35 views

Cross-Entropy VS sum of Binary-Cross-Entropies for multiclass

Most of the classification models that I've encountered so far perform classification using CE loss. For example, if we have 2 possible classes and the GT class is 1, then: the CE loss will be $-\log{\...
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how to caculate 95% CI for AUC? try 384 times or Hanley et al. (1982) method?

I am working on a prediction task to predict heart disease risk. The data size is around 1500 and is splitted into train, validate and test datasets. I am use train dataset to train and use validate ...
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Please help me understand a Figure in Bishop's "Pattern Recognition and Machine Learning", Sec 1.5.1 Minimizing the misclassification rate

The figure is Figure 1.24 on page 40 of Bishop's "Pattern Recognition and Machine Learning", Sec 1.5.1 Minimizing the misclassification rate: I don't understand this figure, starting from &...
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Please help me understand a sentence in Bishop's "Pattern Recognition and Machine Learning"

The sentence is in section 1.5.1 "Minimizing the misclassification rate" (page 39), underlined in red: The author thinks this statement is "clear", but I just can't understand. ...
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Recommendations on litterature for classification problems [duplicate]

I am looking to further my knowledge of algorithms and regression methods for classification problems. What are some resources I should look at/read? Anything you can point me to would be of great ...
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Shop Classification based on two metrics

I'm trying to do a classification analysis in order to classify group of merchants based on their total transaction amount (in USD) and also their total transaction (how many transactions). Notes: ...
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1answer
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Can a classifier be used to improve its own training data?

Introduction: Consider a classification problem of $\mathbb{R}^n$ into $\mathbb{R}^2$. Let $\mathcal{U}$ be a set of instances whose class is unknown, but can be discovered paying a cost $\gamma$ for ...
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Multi-class classification: I am applying an uncertainty threshold to send predictions to human, but I want to statistically determine its usefulness

I have the following prediction scenario: $labels\_true = [0,0,0,0,1,1,1,1,2,2,2,2,3,3,3,3]$ $predictions = [0,0,0,1,1,1,1,0,2,2,2,2,3,3,3,3]$ $uncertainty\_in\_prediction = [0.01, 0.01, 0.02, 0.1, 0, ...
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Is there a feature selection library in Python for multivariate time series classification dataset?

I have a multivariate time series (3D) dataset of the shape, (samples, sequences, features). For instance, (patients, time_sequences_in_hour, features), whereby each sample is a distinct group of time ...
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Applying SMOTE multiple times?

More of a curiosity, but I'm currently learning how to deal with imbalanced datasets and came across the SMOTE method to bias the minority class. The images below show before and after SMOTE was ...
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1answer
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Are non-crossing ROC curves sufficient to rank classifiers by expected loss?

We have two models outputting estimates of class probabilities. Combined with a probability cutoff / threshold, these yield classification decisions: if the estimated probability of class 1 is above ...
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Time steps in RNN and LSTM

I am quite new to recurrent neural networks and how to use them for sequence classification. I was wondering if anyone could shed some light on how RNNs (specifically LSTMs) capture time. That is, can ...
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which classification loss function is relatively not sensitive to the imbalanced sample

I was asked for the question that which classification loss function is relatively not sensitive to the imbalanced sample (tree, regression, e.t.c.)? I know that imbalanced sample will affect the ...
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Test data relevance to a model (covariate shift)

I am trying to design an algorithm that will allow to calculate the relevance of test data to a trained model. This can be done by checking if predictor variables have a different distribution in ...
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Problem Inverse transformation of MultiLabelBinarizer

I am doing a classification problem for that I was having my target column as encoded data, Like this: ...
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1answer
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Bayes error and nearest neighbor classification

Upon studying for my midterm using Pattern Classification by Richard O. Duda, David G. Stork, Peter E.Hart (2001), I stumbled upon the following exercise: Using the solutions manual written by David ...
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1answer
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Why not always use Polynomial Regression to solve classification problems? [closed]

Consider this simple classification problem: You can solve it using Logistic Regression. But there's another way. As @whuber noted in this answer, in hypothesis $h(x) = \frac{1}{1 + e^{-P(x)}}$, ...
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No Free Lunch and regression vs. ELO-like: is it easier to directly estimate if $a$ is better than $b$?

Consider an unknown function $F$, for which we have many examples $F(x_0)=y_0, F(x_1)=y_1,\ldots$. I would like to use these data to estimate whether $F(a) > F(b)$, where neither $a$ nor $b$ are $\...
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Basis of Binary Classification Probability

I am fairly new to Machine Learning and recently I have built a binary classification model and the model architecture is an MLP with two hidden layers. I am predicting, from a protein sequence, the ...
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Are there any methods of testing how well a Gaussian Process fits your data?

Are there any methods of testing how well a Gaussian Process fits your data? I have been looking online and can not seem to find any statistical metrics that measure how well a Gaussian Process (...

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