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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Using confusion matrix to improve my SVM

I ran an SVM classifier on the CIFAR_10 classification workbench. I got about 2/3 accuracy (which I think is Ok, but I want to improve...) Here is my confusion matrix: ...
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Is LinearDiscriminantAnalysis legit for classifying images?

this was moved from SO, hope this is a better place to ask :) on this context: LDA = LinearDiscriminantAnalysis I tried classifying images' descriptors with SVM SVC linear kernel which gave bad ...
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How to not overlook rare but important features when preventing over-fitting in a decision tree?

I have a data set where some binary features divide the sample space roughly in half, whereas other features are much less frequent and occur only for 0.0001 - 0.01 of the sample space. However, those ...
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819 views

Improving multi-label loss function

Trying to train a CNN on a multilabel problem, each image can have 0, 1, 2 or 3 labels assigned to it. The number of labels is not known a priori. I figured the standard loss function for such problem ...
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608 views

Why do my Feature Importance and Partial Dependence plots not agree?

I need some help understanding my partial dependence plots for features passed to a GradientBoostClassifier when comparing them to the feature importances. For some background, my goal here is to ...
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1answer
52 views

85% of the samples come from an unknown distribution, the rest come from the same distribution with a larger variance.How to recognize them?

Assume I have a data, say columns are the samples, and rows are the features, the problem is that around 85% of the samples come from an unknown distribution but the rest come from the same type of ...
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307 views

Interaction effect in random forest

I'm interested in interaction effect between variables in random forest. I found some information here https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm#workings. The operating ...
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486 views

Extract f-statistic from multiple variable regression model and intercorrelated variables

I'm currently analyzing some microarray data (gene expression) and I'm running the kNN classification algorithm on them. Data consisted from 920 different genes and 8 different observations (with 5 ...
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113 views

What information should be released to characterize a dataset for text classification?

I am releasing a dataset for text classification. ​What information would a researcher in natural language processing or machine learning may want to have about this dataset? Here some some ...
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1k views

Classification on highly skewed dataset

I have two classes A and B. 98% of the data belongs to class A and 2% of it belongs to class B. Size of the entire dataset is about 2000. I am interested in correctly classifying all the data points ...
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1answer
63 views

In real clinical diagnostic data set how can we know the “true label” of a patient?

When we were taught about Bayesian probability, we often saw the following example: in a population, there are 5% of people who has disease X, and among the people who have disease X, the current ...
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93 views

Classification: a bayesian network for each class?

Is there a technique for classification, where given a feature vector X = (x_1, x_2,..., x_n) and a Bayesian network for each class, which for each x_1, x_2,...,x_n there may be a corresponding node ...
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658 views

How to build the feature vector from sentence for intent classification in NLU?

I am trying to develop a NLU (natural language understanding) engine which interprets human language utterance to intent and slots. After some searching, I found this very useful question for NLU ...
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Supervised Classification Machine Learning With Video Project

I am just getting into visual machine learning (currently a mobile developer) and have a challenging project of interest. It involves using video as an input to then determine if a baseball player ...
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3answers
2k views

How to select predictor variables for a classification model?

I am running a customer churn predictive model in r. My confusion is when I try different combinations of variables I.e. Removing some from the model, I get completely different results in terms of ...
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528 views

Nearest/farthest neighbour between-group distance: an efficient way to find it

This question might be better suited for StackOverflow as it is programming (so you are free to suggest to move it), but it is about a data analysis programming task. The Q: do you know any "elegant" ...
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How should three unordered categories be encoded in a bayesian network framework?

The SAS FAQ suggest that for unordered two categories I should one dummy variables, for example: The common practice of using target values of .1 and .9 instead of 0 and 1 prevents the outputs of ...
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682 views

R package for classification and outlier detection together

I have a similar problem as this one. My training samples contain N observations and K>2 classes. I want to classify my test samples into one of the K classes, or as an outlier if it is far from any ...
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660 views

Evaluation of a ternary classifier

Are there standard evaluation procedures for non-binary classifiers? In my case I have "nested" classes, being absence and presence of an effect the first and usual binary categorization, but ...
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1answer
853 views

What exactly is the mathematical definition of a classifier / classification algorithm?

I just started an intro machine learning course, and to get things better organized in my head, I was trying to come up with exactly what is needed to completely specify a classification algorithm. I ...
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How to retrain a production classifier that blocks its own positive examples?

I'm looking for help understanding how to re-train a fraud detection classifier that's been deployed to production (where it successfully blocked much, but not all fraud coming into the system). I ...
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433 views

Understanding the approach behind variable importance returned with Xgboost method in R package caret

I recently implemented the R package caret, for a binary categorical outcome regarding a transcriptomic microarray dataset. As i used the method from the xgboost package(method="xgbtree"), then i used ...
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531 views

How to tune the weak learner in boosted algorithms

It is commonly said that boosted algorithms (adaboost, gradient boosted trees) are composed of many "weak" learners. Let's stick to decision trees as the base learners. Some empirical studies ...
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3answers
784 views

Combining one class classifiers to do multi-class classification

I am working on a 3-class classification problem. The classifier I'm using is Bayesian Networks which provides me with a classification accuracy of around 60%. When I do a two-class classification, I ...
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584 views

Understanding calibrating probabilities using R

I am trying to understand R's calibration(package:caret) function. My main interest is binary classification. Calibration function is used for plotting true ...
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1answer
296 views

which classifier to choose for probability histogram-like features

I have a populations of 500 elements. Each element is represented by a 10 dimension feature vector which sum of element is equal to 1 (you can think about it as a histogram of probabilities). In ...
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1answer
2k views

Is the Laplace/Lidstone smoothing parameter (talking about Multinomial/Bernoulli Naive Bayes) related to the particular structure of the dataset?

I'm working with Multinomial and Bernoulli Naive Bayes implementation of scikit-learn (python) for text classification. I'm using the 20_newsgroups dataset. From the scikit documentation we have: <...
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200 views

What is the acceptable event rate to use ROC-AUC instead of precision-recall curve?

It says here However, when dealing with highly skewed datasets, Precision-Recall (PR) curves give a more informative picture of an algorithm's performance. My question is; What is the common ...
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219 views

Add extra class to a pre-trained softmax classifier

Question I'm wondering if some could add an extra class to a pre-trained softmax-ed neural network, trained for multi-class classification problem, without reusing the old training data. Details ...
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64 views

How can I estimate the influence/significance of the every observation on classification?

There are many ways to estimate the significance of the features on the classification model. But how I can estimate the influence of the every observation on the classification quality? My thinking ...
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119 views

Lower classification accuracy after dimensionality reduction

Generally feature selection and dimensionality reduction are recommended to raise classification accuracy. Currently, I am working with datasets from neuroscience which are huge. I have 84 patients, ...
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396 views

How to build “supervised clustering” for neural networks?

I'm confused as to what the output would be. Consider the "blind source separation" problem. Let's say I have a ton of training examples where the input is the final cacophony of sounds as a sound ...
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464 views

Calculating ROC curve for two gaussian distributions with equal variance

I recall a simple formula in a paper which relates the distance between two gaussian distributions (what psychologists refer to as d') to the ROC curve under the assumption that both distributions ...
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327 views

For classification w unbalanced datasets, is class-weighing the same as oversampling?

in unbalanced classification problems, I find myself using class_weigh = "auto" or similar parameters often, but I don't think I'm fully understanding what it's doing. I know that it's the industry ...
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427 views

How to use KL-divergence in naive bayes classifier to weight features?

I have a dataset consisting of 4 classes. I have implemented the Gaussian Naive Classifier (in Matlab). In the training phase I calculate the mean and variance for each feature and each class as well ...
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106 views

Problems with classification in imbalanced datasets

I often read about the problematic of doing classification in imbalanced datasets and methods to address it. Namely, off-the-shelf classifiers learn to minimize some form of total miss-clasffication ...
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3k views

Regression models to only predict integers (instead of floating point numbers)?

I have a dataset that consists of about 50 different attributes. One of these attributes I want to predict, using the other attributes as features. The values of the attribute that I want to predict ...
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1answer
381 views

A statistical test to measure the importance of features?

I'm currently trying to assess importance of the features for my classifier. The situation is the following: first I train my classifier with all of the features I have and tested on a test set . Then ...
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75 views

Ideas to classify shipping addresses

I have a dataset of addresses for a bunch of users. I need to classify an address into residential/commercial or office/educational. Moreover, every user has multiple addresses. So every user has a ...
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Are regression problems more likely to overfit than classification problems?

I will illustrate my question on an example: Let's say we have a dataset that we want to split into two disjoint sets of similar size. The dataset has a high dimensional feature (several hundred ...
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Missing values with Community structure in networks?

Is there a way to predict Missing values with Community structure in networks? I have a data set with a couple dozen variables, such as age, level of education, self-assessed (via a Likert scale) ...
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1k views

Friedman's test to identify best of multiple classifiers on multiple domains

I have several classifiers $f_i (i=1..N)$ and calculated performance measures on multiple domains (D) for each. Thus, there are NxD values. I want to find out (increasing complexity): Is a ...
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1answer
55 views

prediction from incomplete observations

Suppose I have a linear model predicting class-membership from a set of predictors. Now, I am going to classify a new observation which has, however, some predictor values missing. How can I deal with ...
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253 views

Time series prediction where each datapoint has a sequence

I am Computer Science major, and new to stats, so please bear with me and point me to the right direction if what I'm asking is pretty obvious. I have a dataset, where each data point consists of <...
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222 views

What are some classic examples of feature selection in classification?

Is there a classic example showing the importance of good feature selection in classification? The ideal example would be simple, and very easy to understand. I've been volunteered/instructed to put ...
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Probability extraction from random forest classifier

I have a random forest to perform classification. I need the real probability of the predicted class. They take a feature vector X and output a predicted class C. Additionally we can compute the ...
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727 views

Clarification on LDA and the multivariate Gaussian

From my understanding, to calculate the posterior probability of a sample $x$ belonging to a class $k$ using Linear Discriminant Analysis you would first calculate the eigenvector matrix $W$ required ...
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371 views

Wide swings in SVM performance with different training/test sets

I'm trying to train a classifier on 10 classes, using 249 samples and a (currently) 16-dimensional feature vector. I'm using an SVM with RBF kernel, through Python's scikit-learn module. The ...
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345 views

Linear Discriminant Analysis: Using subject as classification

I have a problem where I need to identify from which subject a particular set of data points came. More specifically, my problem is that I need to demonstrate that my subjects (N=9) can be ...
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How to use reservoir states for readout and training?

I’m trying to make a Liquid State Machine, I have a spiking neural network as the liquid, and a feedforward neural network that should learn to map the reservoir’s states to the output. I’ve read ...