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, .

Filter by
Sorted by
Tagged with
18 votes
1 answer
4k views

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 ...
user avatar
17 votes
2 answers
10k views

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 ...
user avatar
16 votes
2 answers
2k views

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 ...
user avatar
  • 283
16 votes
4 answers
2k views

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, ...
user avatar
10 votes
3 answers
622 views

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 ...
user avatar
  • 305
8 votes
2 answers
392 views

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 ...
user avatar
8 votes
2 answers
363 views

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 ...
user avatar
  • 83
7 votes
1 answer
764 views

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 ...
user avatar
  • 173
7 votes
5 answers
8k views

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, ...
user avatar
7 votes
2 answers
566 views

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 ...
user avatar
7 votes
1 answer
1k views

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 ...
user avatar
  • 323
7 votes
1 answer
146 views

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 ...
user avatar
6 votes
2 answers
650 views

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 ...
user avatar
  • 61
6 votes
1 answer
267 views

How to add more features to the input of a machine learning algorithm?

I am trying to perform a binary classification of tweets using machine learning. The usual way of doing this seems to be putting a hand-classified tweet's words into a big vector, then use that ...
user avatar
  • 245
6 votes
2 answers
93 views

Two data classes for a convolutional neural network, can one have a LOT more images for training than the other?

I have two classes in the training set: one that has images with a feature and the other of images without that feature. Can there be a LOT more images with "no feature" so I can fit in all possible ...
user avatar
  • 69
6 votes
0 answers
97 views

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 ...
user avatar
6 votes
1 answer
90 views

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. ...
user avatar
  • 91
5 votes
2 answers
518 views

How does text classification reduce manpower costs?

(I apologize for the title being too broad and the question being not 'technical') Suppose that my task is to label news articles. This means that given a news article, I am supposed to classify ...
user avatar
5 votes
2 answers
155 views

How do I improve accuracy and know when to stop training?

I am training a modified VGG-16 to classify crowd density (empty, low, moderate, high). 2 dropout layers were added at the end on the network each one after one of the last 2 FC layers. network ...
user avatar
  • 115
5 votes
3 answers
98 views

Do specific units exists for measuring the intelligence of a machine?

We can measure the power of the machine with the number of operation per second or the frequency of the processor. But does units similar of IQ for humans exist for a AI? I'm asking for a unit which ...
user avatar
  • 51
5 votes
2 answers
1k views

Should the prediction of the body temperature given a camera image be modelled as classification or regression?

I am fairly new to deep learning in general and I am currently facing a problem I want to solve using neural networks and I am unsure if it is a classification or regression problem. I am aware that ...
user avatar
5 votes
2 answers
3k views

Is it possible to classify data using a genetic algorithm?

Is it possible to classify data using a genetic algorithm? For example, would it be possible to sort this database? Any example in Matlab?
user avatar
5 votes
3 answers
214 views

How to make convnets aware what the image actually is, not what is depicted on it?

I've uploaded a picture to Wolfram's ImageIdentify of graffiti on the wall, but it recognized it as 'monocle'. Secondary guesses were 'primate', 'hominid', and 'person', so not even close to 'graffiti'...
user avatar
  • 10.1k
5 votes
1 answer
2k views

What is the difference between imitation learning and classification done by experts?

In short, imitation learning means learning from the experts. Suppose I have a dataset with labels based on the actions of experts. I use a simple binary classifier algorithm to assess whether it is ...
user avatar
5 votes
4 answers
597 views

What kind of neural network architecture do I use to classify images into one hundred thousand classes?

I have an image dataset where objects may belong to one of the hundred thousand classes. What kind of neural network architecture should I use in order to achieve this?
user avatar
5 votes
3 answers
483 views

How does neural network classifier classify from just drawing a decision plane?

I understand that a neural network basically distorts(non-linear transformation) and changes the perspective(linear transformations) of input space to draw a plane to classify data. How does the ...
user avatar
  • 316
5 votes
1 answer
135 views

How do I statistically evaluate a ML model?

I have a model that predicts sentiment of tweets. Are there any standard procedures to evaluate such a model in terms of its output? I could sample the output, work out which are correctly predicted ...
user avatar
  • 245
5 votes
3 answers
185 views

Is it better to make neural network to have hierchical output?

i'm quite new to neural network and i recently built neural network for number classification in vehicle license plate. It has 3 layers: 1 input layer for 16*24(382 neurons) number image with 150 dpi ,...
user avatar
  • 105
5 votes
2 answers
111 views

What should the range of the output layer be when performing classification?

I am working on a MLP neural networks, using supervised learning (2 classes and multi-class classification problems). For the hidden layers, I am using $\tanh$ (which produces an output in the range $[...
user avatar
  • 121
5 votes
1 answer
254 views

Methods to tell if a question can be answered from a paragraph

I'm working on a project related to machine Q&A, using the SQuAD dataset. I've implemented a neural-net solution for finding answers in the provided context paragraph, but the system (obviously) ...
user avatar
  • 51
5 votes
1 answer
291 views

Detect patterns in sequences of actions

I have to analyse sequences of actions that look more or less like this JSON blob. The question I'm trying to answer is whether there are recurring (sub)patterns that different users adopt when asked ...
user avatar
  • 101
5 votes
1 answer
117 views

How to classify human actions?

I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses). I want to classify human actions real-time like: Left-arm bended Arm above ...
user avatar
4 votes
4 answers
150 views

How to classify language as friendly or aggressive with AI?

Just for the purpose of learning I'd like to classify the likeliness of a tweet being in aggressive language or not. I was wondering how to approach the problem. I guess I need first train my neural ...
user avatar
  • 223
4 votes
3 answers
2k views

Can I do image classification with Multi Layers Perceptron (MLP)?

I'm seeking guidence here. Can I use Multi Layers Perceptron (MLP), e.g regular flat neural networks, for image classification? Will they perform better than Fisher Faces? Is it difficult to do ...
user avatar
  • 143
4 votes
1 answer
2k views

Can I train a neural network incrementally given new daily data?

I would like to know if it was possible to train a neural network on daily new data. Let me explain this more in detail. Let's say you have daily data from 2010 to 2019. You train your NN on all of it,...
user avatar
4 votes
3 answers
16k views

How to "combine" two images for CNN input (classification task)?

For a classification task (I'm showing a pair of exactly two images to a CNN that should answer with 0 -> fake pair or 1 -> real pair) I am struggling to figure out how to design the input. At the ...
user avatar
  • 256
4 votes
1 answer
130 views

How to define machine learning to cover clustering, classification, and regression?

How to define machine learning to cover clustering, classification, and regression? What unites these problems?
user avatar
  • 171
4 votes
1 answer
256 views

How is the formula for the Bayes error rate with an integral derived?

My questions concern a particular formulation of the Bayes error rate from Wikipedia, summarized below. For a multiclass classifier, the Bayes error rate may be calculated as follows: $$p = 1 - \sum_{...
user avatar
4 votes
1 answer
862 views

Can neural networks with a sigmoid as the activation function of the output layer approximate continuous functions?

Neural networks are commonly used for classification tasks, in fact from this post it seems like that's where they shine brightest. However, when we want to classify using neural networks, we often ...
user avatar
  • 505
4 votes
2 answers
166 views

Is there any difference between the convolution operation applied to images and applied to other numerical 2D data?

Is there any difference between the convolution operation applied to images and applied to other numerical 2D data? For example, we have a pretty good CNN model trained on a number of $64 \times 64$ ...
user avatar
4 votes
1 answer
106 views

Decision tree: more than 2 classes, how to represent elements that are in a class vs ones that aren't?

I'm building a decision tree and would like to separate (for example) the elements that are in class 0 from those in classes 1 and 2, case in point: ...
user avatar
4 votes
1 answer
487 views

How should I deal with variable input sizes for a neural network classifier?

I am currently working on a project, where I have a sensor in a shoe that records the $X, Y, Z$ axes, from an acceleration and gyroscope sensor. Every millisecond, I get 6 data points. Now, the goal ...
user avatar
  • 41
4 votes
2 answers
87 views

Is there any classifier that works best in general for NLP based projects?

I've written a program to analyse a given piece of text from a website and make conclusary classifications as to its validity. The code basically vectorizes the description (taken from the HTML of a ...
user avatar
4 votes
1 answer
81 views

Is there any measure of separability of classes?

I want to know if there is a measure of how well two classes in Y are separable (linearly or not) based on their features in X. Easiest way of explaining this is to compare it to correlation ...
user avatar
  • 1,039
4 votes
1 answer
123 views

How to define a loss function for a classifier where the confusion between some classes is more important than the confusion between others?

I have a dataset of images belonging to $N$ classes, $A_1, A_2...A_n,B_1,B_2...B_m$ and I want to train a CNN to classify them. The classes can be considered as subclasses of two broader classes $A$ ...
user avatar
  • 269
4 votes
1 answer
42 views

How to design a classifier while the patterns of positive data are changing rapidly?

In some situation, like risk detection and spam detection. The pattern of Good User is stable, while the patterns of Attackers are changing rapidly. How can I make a model for that? Or which ...
user avatar
  • 143
4 votes
1 answer
857 views

Is it possible to train a neural network to identify only one type of object?

I am new to neural networks. Is it possible to train a neural network to identify only one type of object? For instance, a table from a large set of images, where the neural network should be able to ...
user avatar
4 votes
1 answer
390 views

Why does the binary cross-entropy work better than categorical cross-entropy in a multi-class single label problem?

I was just doing a simple NN example with the fashion MNIST dataset, where I was getting 97% accuracy, when I noticed that I was using Binary cross-entropy instead of categorical cross-entropy by ...
user avatar
4 votes
2 answers
109 views

What is the best way to find the similarities between two text documents?

I would like to develop a platform in which people will write text and upload images. I am going to use Google API to classify the text and extract from the image all kinds of metadata. In the end, I ...
user avatar
4 votes
1 answer
165 views

Video engagement analysis with deep learning

I am trying to rank video scenes/frames based on how appealing they are for a viewer. Basically, how "interesting" or "attractive" a scene inside a video can be for a viewer. My final goal is to ...
user avatar
  • 963

1
2 3 4 5
8