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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Can you help me to understand this deduction for proving Naive Bayes is a Linear Classifier?
In this tutorial on Naive Bayes Classififer in section 1.1, the author proved naive bayes is a linear classifier.
Consider binary classification where $y=0$ or $1$. Our classification rule with ...
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Should I balance my training dataset for an employee attrition analysis in machine learning?
I need to perform an analysis on employee attrition using Machine Learning algorithms. I intend to do both Supervised Learning ...
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How can we best utilize the knowledge of P(y=1) in classification? [duplicate]
Premise
I saw an interesting example of a machine learning logistic classifier for modeling/predicting sentiment for customer reviews. One of the first things in the example was a note on ...
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Extract features from a questionnaire
I am using the answers from a questionnaire for a classification problem.
I discovered that a question can have nested sub-questions..
Let's say that I want to predict the age of a student based on ...
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Temporal Distance Intervals Classification Task
I was reading a paper Playing hard exploration games by watching YouTube https://arxiv.org/abs/1805.11592.
By my understanding the authors use convolutional neural networks to generate embeddings ...
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Training a classifier on 2 catalogs combined
I'm currently trying to train a machine to identify flashes of light in the sky as supernova (SN) or not. To do this, I'm combining 2 different catalogs:
A big catalog (99% SN) with brighter flashes ...
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Classify a specific object amongst other diverse objects
I have a device which takes one picture per day of a slab. It contains many instances of a specific object (let's call it "Object A") and a few other objects (let's call them "Others").
I want to ...
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why the kernel size become greater as the spatial size of feature map goes down in inception network？
In the inception networks like inception-v3 and inception-v4, the kernel sizes are smaller in the lower layers,such as 3*3, but in the higher layers, the kernel sizes seem to be larger,such as 5*5,7*7,...
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How to evaluate the performance of a predictor on an unlabelled dataset? What is an appropriate test set size and how to sample it?
I am working on a project with goal to deduplicate a customer database. We don't have any annotations (no training/test set with the ground truth values).
We implemented multiple unsupervised ...
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Discriminant Analysis: Explicitly writing Covariance matrix given some sample data
Let $(X, Y) \in \mathbb{R}^d \times \{0, 1\}$ give a random pair wherein the conditional distribution of $X$ given $Y$ is $X | Y \sim \mathcal{N}(\mu_Y, \Sigma_Y)$, $\mu_0 \neq \mu_1 \in R_d$, where $\...
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Performance of classifier with positive, negative, and unlabeled data
The problem
I have a dataset where ca. 90 % of the dataset is unlabeled and the rest is positively and negatively labeled (unbalanced).
I want to describe the performance of a classifier on this ...
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Multilabel classification versus yes/no classification for each class (with label priority)? [duplicate]
NOT A DUPLICATE. These questions are related, but mine is asking about a specific application of classifiers - flagging Stack Exchange posts. I want to know which of the 2 methods is most effective ...
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Cluster analysis with boosting models for better predictions?
let's say that we have a simple, binary classification problem (with many predictors and many observations) and want to fit for example some kind of boosting algorithm to obtain resutls. Let's also ...
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Get test and traininig data set by using cross validation
I have a data sets and want now find a model to predict wages.
I read that just cutting the data sets into 2 parts by a percentage number to get the training and test data set is not efficient. ...
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A better way to compare accuracy?
Hi I have an algorithm that takes a single sample, call it i and tries to predict what other samples in a cohort it is most closely related to. This cohort consist of N=11K from different tissues. ...
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Appropriate statistical or machine learning measure to find important IDs within array of t-tests
I have an array of data that contains ~600 protein name identifiers, and each ID holds an accompanying four hundred t-test scores from interrelated experiments. So it's a 600x400 matrix, let's say.
I'...
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How to Optimize Predictive Classification Model for Lead Time
How do I optimize a predictive classification model to reward variables and values that give predictions earlier in sequential data?
For example:
Let's say I'm modelling whether an upcoming ...
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Statistical difference of machine learning predictions
I am applying a machine learning classification method to two difference scenarios for my boss (in this context, I am using a random forest). Due to the nature of the problem, there is high class ...
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Classification/Prediction based on Multivariate Time Series
So, I have a time series with many independent variables (X's) and an outcome variable Y (that I want to predict, think a 2 class logistic regression where output would either be 1 or a 0). Kindly see ...
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Adding new samples to dataset
Consider the situation where we have a trained classifier (which isn't dramatically over/underfitted) that we want to improve, and lots of unlabeled data readily available, and we would like to spend ...
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Great ways to identify adult content in text
What are some good ways to identify adult content in text. It is definitely a text classification problem, but how do we handle words that are spelt like @$$.
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PCA variances pattern changed greatly after data cleaning
I have data, when I normalize it and then performed PCA, I calculated the variance of PC components, I found that, the first component is 72% and seconed component is 8% (total 72+8=80%) and so on.
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How to do one-class classification?
I am working on a classification model for crop detection. Let say I have the data of wheat only. I want my classifier to recognize its pattern and after providing a new data set, it should tell me ...
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Best labelled dataset for training a binary image classifier
I want to train some binary classifiers in Keras (e.g. to decide if there is person on a picture or if there is a vehicle on it). What is the best dataset to use for this? I mean datasets like these. ...
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Decting new classes (open world classification)
In real world applications very often the entire set of classes is not known during the training phase (e.g. identifying objects, sounds, etc.). A system is needed that can classify observations into ...
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Fingerprint at scale - what is the state of the art?
I'm working on a problem of fraud detection in account opening. When a new user opens an account, we compare a set of three fingerprints against entries in an existing database.
The existing database ...
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Log loss when classes are -1 and +1 [duplicate]
We can calculate the log loss for a classification problem with two classes as follows:
where y is the label of the actual class and ...
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What are some potential reasons for no significant difference between Random Feature Selection and Automatic Feature Selection?
Basic info abut the experiment:
Binary classification of exons
10 fold cross validation
1200 features of exons are ranked by Fisher Score, Relief and Gini Index feature selection algorithms
1-...
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Multi-label classification, binary loss concerns
I am solving a multi-label audio classification task with neural networks. The dataset is comprised of 10 classes, and the input data to the network are audio files where two of these classes are ...
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Neural Networks: How to do class prediction from murky labels
I'm conducting an experiment with the MNIST digit data - handwritten digits 0-9, each example composed of 28x28 bitmap of pixels.
Imagine a collection of examples is drawn at random without class ...
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Optimal Parameter for Binary Classifier
If I have a binary letter classifier for the letter "I" which classifies using the sum of all pixels in a picture. The parameter that is input to the classifier decides its classification.
MATLAB CODE:...
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CART selection and *deselection* classification tree
I came across a line in Peterson, et al. (2016) that says:
The specific settings applied in the rpart procedure ensured that only the largest subgroup would be ...
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Weight minority classes using XGBoost (Multiclass)
I'm dealing with a multiclass problem in R using XGBoost. The dataset has 3 Classes representing the following proportion: 20% - 75% - 5%.
Given the description above, it would be awesome some tips ...
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Multi-label classification with Neural networks
Task:
Multi-label classification of sounds using neural networks. (Urbansound8K Dataset)
Problem:
How to best generate my combined dataset, considering maximum 2 sounds combined at the same time.
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Training of multiple time-series with different lengths
I have a lot of time series with different lengths. I would like to know what are the best practices to fit them to a Bidirectional LSTM model. The problem is a Binary Classification of Sequence to ...
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Splitting Data Into Training and Test set
I am trying to split a data set into training and test set with these codes
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logistic regression with two-sided covariate
I want to do a logistic regression, with multiple covariates, where at least one of the covariates is two-sided. When I say that a covariate $x_1$ is "two-sided", I mean that values close to the mean ...
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How can I use real valued labels in training a CVAE?
The Conditional Variational Autoencoders (CVAE) (and other classification networks) I have come across use a one hot vector encoding for labeling categorial data sets.
In my case, I do not have a ...
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Information Gain and attributes
In the book i'm reading about Data Mining, in the chapter about decision tree it's said that the information gain test is biased towards tests with many outcomes (attributes having a large number of ...
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Classification threshold selection for predictions on unseen data
In binary classification, what is the optimum probability threshold to predict binary outcomes (0/1) on unseen data without knowing the actual outcome?
Let's assume that a random forest model has ...
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Classification using an ensemble of decision trees
I am going through some theory regarding classification using multiple decision trees. Note that a tree has probabilities of classes on each of its leaves . Here's the equation:
P(y' = $\omega$ | x', ...
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Multi-label classification: overlapping or graph structure among labels
I am doing multi-label text classification. I have 5000 classes and there is a graph structure among these classes.
How to deal with multi-label classification where there is overlapping or graph ...
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Classification with 500 Categories
Currently I am working on several projects with classification algorithms. The number of categories is very high (between 100 and 4 000, but let us assume it is 500).
Which algorithms are suitable ...
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Classification on multivariate time series
My dataset:
121 individuals characterized by a categorical variable let’s say Y (so 121 values of Y)
for each individual, I have 5 time series, let’s say X1, X2, X3, X4, X5.
each time series contains ...
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Bayesian framework for artificial neural networks in classification?
I am trying to understand the probabilistic concepts behind classification using neural networks, for the goal of incorporating prior information over the target class distributions.
I am failing to ...
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Find a cost-sensitive multiclass algorithm
I am working on decision trees which can directly work in a multiclass context. My aim is reduce the misclassification's errors of a decision tree by improving its ability to tackle imbalanced ...
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Optimal value for the intercept term in SVM
(note that this problem is different from this one, since the latter considers primal's Lagrangian)
Hi,
I am trying to figure out the SVM's dual problem. The primal problem is
$${\displaystyle {\...
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Optimal degree and C parameter in Polynomial SVM
Okay I know that there are a lot of posts out there about the C parameter in SVM, but I had a quick question about this.
In Polynomial SVM (Which I'll be coding in Python), I can set the parameters ...
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What is monotonic classification?
I read this about student surveys:
Student surveys occupy a central place in the evaluation of courses at
teaching institutions. At the end of each course, students are
requested to evaluate ...
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