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Questions tagged [supervised-learning]

Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.

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Which technique is most appropriate for identifing various sentiments in the same text using python?

I'm studying NLP and as example I'm trying to identify what feelings are in customer feedback in the online course platform. I was able to identify the feelings of the students with only simple sentence, such as "The course is very nice, I learned a…
Kadu
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Is there any unsupervised learning algorithm that do not not assign k

A traditional unsupervised learning approaches normally needs to assign number of clustering (K) before computing, but what if I do not know the exact number of K and exclude the k out of algorithm, I mean, Is there any unsupervised learning…
bricker
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Machine learning - how to infer the colour of a car from a car image

I want to train a model to infer the colour of a car from a car image. Let's say that for the colour classification I will use the k-nearest neighbours algorithm. Let's also suppose that: 1) I have 1000 labelled images 2) I have 100 images for…
Outcast
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How to do dimension reduction in Bag of Words for a Classification Model using Random Forest

I am using Text data Features along with other numerical features for classification model. How can I group similar bag of words together in a supervised classification Model. How I can group similar words after countvectorizing , I want reduce…
aeapen
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Decrement learning rate in error back propagation algorithm

This is more or less general question, in my implementation of backpropagation algorithm, I start from some "big" learning rate, and then decrease it after I see the error started to grow, instead of narrowing down. I am able to do this rate…
Павел
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What is the best model for facial expression classification in videos?

I am looking for the State of the art deep learning model for facial expression classification in videos. Given an Input video, I want the algorithm to detect the faces in them and classify the emotion associated to that face. The emotions that I…
Kousik Krishnan
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How to come up with questions on supervised and unsupervised learning?

I am new to data mining concepts and trying to learn the differences between supervised and unsupervised learning. So far what i know is that supervised means getting the information from labeled datasets and unsupervised means clustering the data…
Taran Rai
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Have Pixel based labeled gray images data. Any suggest to train this data for classification?

I have pixel by pixel based labeled (5 label classes 0, 1, 2, 3, 4) data of around 200,000 images. Each image sized 240x240. Can anyone suggest me how can I train this data efficiently and what will be the best possible classification method for…
Ghazanfar Latif
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how to classify .txt documents into some other .txt categories by supervised learning

I've got about thousands of txt documents stored in 8 different file folders which are tagged with topic categories (actually,they are class 1,2,3...). And I have another 80 txt documents that don't yet have categories. I'm trying to find the best…
Andy Zhao
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Wondering which percentage below it we can say the class is not balanced?

I am sure here there is someone who has experienced something like this... I have a dataset with 4 classes, one of it is 3% representation and I considered it as under-represented, so I did some resampling approaches, but guess what? its…
mhdella
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How to print out to a file using Stanford Classifier

I am using Stanford Classifier for my project. This project takes training data to tune the algorithm then test data to classify text inputs into categories. So the format for test and training data is tab-delimited text which means predictor -TAB-…
Nebi M Aydin
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How do i improve the efficiency of a supervised machine learning algorithm

I'm working on a project which involves the use of a sequential supervised machine learning model,which i am using to extract data from unstructured text data.The diversity of the data is vast. So,i'm planning to create a training set with huge…
Gobi S
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how to find surrogate of a non convex function

I am doing learning to rank.I have found that some of the loss functions for example 0/1 loss can not be directly minimized being either non-convex or discontinuous etc.this is true in case of other loss functions also. So the researchers use…
wazih ahmad
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how to classify the whole data set in weka

I've got a supervised data set with 6836 instances, and I need to know the predictions of my model for all the instances, not only for a test set. I followed the approach train-test (2/3-1/3) to know about my rates TPR and FPR, and I've got the…
Txus Lopez
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Selecting samples for supervised machine learning

How does one select a sample size and sample set (for training and testing) for a binary classification problem to be solved by applying supervised learning? The current implementation is based on 15 binary features which we may expand to 20 or…
Parag Ahire
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