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, .

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80 views

Problem with the PLN classifier

I'm developing a chatbot, and to get the answer I'm using the Naive Bayes classifier by sorting the questions and answers. For those who want to see the whole project code and more definitions follow ...
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295 views

CNN attention maps on non-images

My datasets are not actual images, so using methods with ImageDataGenerator or pre-trained networks might not apply in this case. Data Structure: Each "image" is a 2048-long vector that has float ...
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3answers
734 views

Ensemble Learning using Convolutional Neural Networks

I have created 22 different Convolutional neural networks that all test for the presence of unique objects in an image (each one of the classifiers is unique). Each sample in the test set has the ...
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1answer
100 views

Extracting multiple softmax values from image

I am currently in the pre-process of starting an image classification and extraction project which needs to output multiple softmax and absolute values from a single image like such: ...
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1answer
540 views

Multi-Label Image Classification using KNN

I'm not quite sure how I should go about creating a multi-label image KNN classifier using python as a lot of the literature I have read does not explicitly explain this methodology. Specifically, I ...
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1answer
232 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 ...
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2answers
2k views

Spam Detection using Recurrent Neural Networks

I am working on this code for spam detection using recurrent neural networks. Question 1. I am wondering whether this field (using RNNs for email spam detection) worths more researches or it is a ...
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1answer
2k views

Multi-label Classification with non-binary outputs

I am looking to train a dataset that would output a sequence of letters (I'm using this for peptide sequences). Since I have 22 different possibilities of amino acids, I need to output a vector that ...
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1answer
107 views

What algorithms are used for segmentation and classification of non solid regions in an image?

In the process of segmentation, pixels are assigned to regions based on features that distinguishes them from the rest of the image. Value Similarity and Spatial Proximity, for example, are two ...
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3answers
8k 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 ...
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3answers
577 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 ...
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0answers
66 views

Is there a measure of AI relative strength, modified by resources?

For instance Strength/Size*Speed, where size and speed refer to memory and processing. We now have very strong, narrow AI, but they tend to run on fast hardware without volume restrictions. To ...
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2answers
3k views

Why has cross entropy become the classification standard loss function and not Kullbeck Leibler divergence?

Cross entropy is identical to the KL divergence plus entropy of target distribution. KL equals to zero when the two distributions are the same, which seems more intuitive to me than the entropy of the ...
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1answer
187 views

GA rule discovery fitness function

I'm attempting to develop a genetic algorithm capable of discovering classification rules for a given data set, a number of papers make use of the Confidence (precision) and Coverage of a rule to ...
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2answers
888 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 ...
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1answer
89 views

What are examples of AI that use philosophy derived ontologies?

I'm looking for AI systems or natural language processors that use, in the classification and interrelation of notions/objects, some philosophical system, like basic laws of logic, Kantian or ...
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1answer
78 views

Using AI to interpret the nature a specific input and use the correct model.

How would one go about building an AI that is capable to look at any kind of input and then identify what is the nature of this data? For example, an AI that is able to do image classification, NLP ...
3
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1answer
106 views

How many training example text classifier needs to be trained?

I want to train text classifier (using https://www.uclassify.com) with 12 classes/categories. I will be training it to classify news/articles (I know that there are existing classifier but I want to ...
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2answers
1k 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?
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1answer
403 views

Why do action recognition algorithms perform better on ucf101dataset than HMDB51 dataset?

If we look at state of the art accuracy on the UCF101 data set, it is around 93% whereas for the HMDB51 data set it is around 66%. I looked at both the data sets and both contain videos of similar ...
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0answers
95 views

Infer dependent variables to produce output aligned to trained data

Hypothetical example, say I wanted: P(gender,ethnicity|age,hair); so that the input would aligned to a trained dataset of: ...
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2answers
648 views

What algorithm should I use to classify documents?

I'd like to build a program that would learn to automatically classify documents. The principle would be that, for each new document I add to the system, it would automatically infer in which category ...
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1answer
489 views

Bag-of-Words (BoW) model in image detection

Any good example for Bag-of-Words (BoW) model in image retrieving? I want a simple example to understand the whole process of BoW.
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1answer
102 views

What is the most effective way to build a classifier?

At the moment I am working on a project which requires me to build a naive Bayes classifier. Right now I have a form online asking for people to submit a sentence and the subject of the sentence, in ...
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1answer
3k views

How to calculate entropy for an ID3 decision tree?

Wikipedia's description of entropy breaks down the formula, but I still don't know how to determine the values of X and p(x), defined as "The proportion of the number of elements in class x to the ...
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4answers
7k views

How to classify data which is spiral in shape?

I have been messing around in tensorflow playground. One of the input data sets is a spiral. No matter what input parameters I choose, no matter how wide and deep the neural network I make, I cannot ...
2
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1answer
86 views

Using feature learning for a medical text classification problem [closed]

I'm currently working with the CHILDES corpus trying to create a classifier that distinguishes children whom suffer from specific language impairment (SLI) from those who are typically developing (TD)....
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3answers
203 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'...
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1answer
161 views

How does Wolfram's Image Identification Project work?

Wolfram Language Image Identification Project launched an Image Identify site demo which returns the top predicted tags for the photos. How does it work, briefly? I mean what type of learning vision ...
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1answer
213 views

How does Pinterest decipher what's on unmarked pictures and categorize them?

According to this article, Pinterest acquired VisualGraph, an image recognition and visual search technology startup. How does Pinterest apply VisualGraph technology for machine vision, image ...
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0answers
107 views

Why does my NN not classify these tic tac toe pattern correctly? [closed]

I'm trying to teach an AI different pattern of tic tac toe to recognize wether a given pattern represents a win or not. Unfortunately it's not learning to recognize them correctly and I think may way ...
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2answers
2k views

How successfully can convnets detect NSFW images?

For example, search engine companies want to classify their image searches into 2 categories (which they already do that) such as: NSFW (nudity, porn, brutality) and safe to view pictures. How can ...
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4answers
114 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 ...
2
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1answer
336 views

Can ConvNets be used for real-time object recognition from video feed?

Convolutional neural network are leading type of feed-forward artificial neural network for image recognition. Can they be used for real-time image recognition for videos (frame by frame), or it takes ...
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3answers
74 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 ...
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1answer
253 views

How do Google cars recognize the traffic signs?

The paper Multi-column Deep Neural Networks for Image Classification (pages 7-8) shows an attempt at recognizing the traffic signs, with lower error rates, by using multi-column deep neural networks. ...