Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [classification]

For questions related to the placement of individual cases into categories, such as is essential in fraud detection, spam detection, quality control, prediction of user or market responses, automated organizing or indexing, assigning objects in view to types of obstacles or risks, writing or typing recognition, phonic recognition, .

Classification is the automatic categorization of a new observation. This classification is based on a model produced from a training set of data containing observations whose classifications are given. Classification is especially useful for problems involving categorical data.

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How to implement an "unknown" class in multi-class classification with neural networks?

For example, I need to detect classes for MNIST data. But I want to have not 10 classes for digits, but also I want to have 11th class "not a digit", so that any letter, any other type of image, or random noise would be classified as "not a digit".…
Sergey Kravchenko
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Why has the cross-entropy become the classification standard loss function and not Kullback-Leibler divergence?

The cross-entropy is identical to the KL divergence plus the entropy of the target distribution. The KL divergence equals zero when the two distributions are the same, which seems more intuitive to me than the entropy of the target distribution,…
Josh Albert
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What makes neural networks so good at predictions?

I am new to neural-network and I am trying to understand mathematically what makes neural networks so good at classification problems. By taking the example of a small neural network (for example, one with 2 inputs, 2 nodes in a hidden layer and 2…
Aditya Gupta
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When is deep learning overkill?

For example, for classifying emails as spam, is it worthwhile - from a time/accuracy perspective - to apply deep learning (if possible) instead of another machine learning algorithm? Will deep learning make other machine learning algorithms like…
Alexander
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Can machine learning algorithms be used to differentiate between small differences in details between images?

I was wondering if machine learning algorithms (CNNs?) can be used/trained to differentiate between small differences in details between images (such as slight differences in shades of red or other colours, or the presence of small objects between…
The Pointer
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Do I need classification or regression to predict the availability of a user given some features?

While studying data mining methods I have come to understand that there are two main categories: Predictive methods: Classification Regression Descriptive methods: Clustering Association rules Since I want to predict the user availability…
Guest2000
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Can a deep neural network be trained to classify an integer N1 as being divisible by another integer N2?

So I’ve been working on my own little dynamic architecture for a deep neural network (any number of hidden layers with any number of nodes in every layer) and got it solving the XOR problem efficiently. I moved on to trying to see if I could train…
bigphil
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Binary classifier that minimizes false positive error

I have a binary classification problem, where a false positive error has a very big cost compared to the false negative error. Is there a way to design a classifier for such problems (preferably, with an implementation of the algorithm)?
ayyoob imani
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How to determine if an Amazon review is likely to be fake using text classification

I'm currently in the research stage of building a web app in ASP.NET where the user can input a URL to an Amazon product, then the app would determine how likely its reviews are to be genuine. I need help figuring out what algorithm to use in…
user8709398
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What algorithms are used for image segmentation of images where objects are not composed of pixels that are similar in value?

In the process of segmentation, pixels are assigned to regions based on features that distinguish them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two important principles that assume that points in the same…
user7369
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How can a neural network distinguish a rotated 6 and 9 digits?

Rotated MNIST is a popular dataset for benchmarking models equivariant to rotations on $\mathbb{R}^2$, described by $SO(2)$ group or its discrete subgroups like $\mathbb{Z}^{n}$: Group equivariant convolutional networks Harmonic networks It…
spiridon_the_sun_rotator
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How should the neural network deal with unexpected inputs?

I recently wrote an application using a deep learning model designed to classify inputs. There are plenty of examples of this using images of irises, cats, and other objects. If I trained a data model to identify and classify different types of…
Jeff
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Can training a model on a dataset composed by real images and drawings hurt the training process of a real-world application model?

I'm training a multi-label classifier that's supposed to be tested on underwater images. I'm wondering if feeding the model drawings of a certain class plus real images can affect the results badly. Was there a study on this? Or are there any past…
user
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How to use BERT as a multi-purpose conversational AI?

I'm looking to make an NLP model that can achieve a dual purpose. One purpose is that it can hold interesting conversations (conversational AI), and another being that it can do intent classification and even accomplish the classified task. To…
junfanbl
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Can neural networks learn to ignore an input datum?

Disclaimer: I'm not a student in computer science and most of my knowledge about ML/NN comes from YouTube, so please bear with me! Let's say we have a classification neural network, that takes some input data $w, x, y, z$, and has some number of…
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