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.
Questions tagged [supervised-learning]
542 questions
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Numerical and Categorical Features in classification problem
I have a classification problem to figure out hotel cancellations (in python).
I'm stuck in a problem of the first steps.
I have some variables regarding hotel reservations, and some of them are:
ArrivalDateYear: Year of the arrival…
Marteusa
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How to evaluate how similar 5 datapoints are to 1 target datapoint
I am struggling to wrap my head around a problem I need to resolve.
Say that we have a cars dataset (1) with many different cars that have different features (id, age, mileage, color, model,...). On the other hand, we have another dataset (2) with…
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Do unsupervised machine learning model features need to be independent?
I'm training an unsupervised machine learning model and want to make sure my features are as useful as possible!
Do unsupervised machine learning model featured need to be independent? For example, I have a feature (subscriptionId) that is the…
mangokitty
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Can we train of a binary classifier with "A" to classify "a"?
I have a maybe naive question of the appropriateness in the use of binary classification. This is a hypothetical example, so forgive me if it is too coarse.
Let’s say I want to train a support vector machine to classify the letter "a" from the…
PPM
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Train data and test data that have target column
I'm trying to make some predictive model using Baking Dataset - Marketing Targets from kaggle here is the link : https://www.kaggle.com/datasets/prakharrathi25/banking-dataset-marketing-targets
The dataset from kaggle already been separated into…
Jovian Aditya
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Decision Trees in Random forest Algorithm
Hi I'm a beginner to random forest algorithm in Machine Learning.
According to what I have read in theory, it works on majority vote concept for classification problems. But can it be possible that number of "Yes" is same as number of "No"?
What…
ZAbbas
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Python XGBoost Regressor Error: Feature_names mismatch
I'm trying to use XGBoost Regressor to predict revenue, given some input features. However, I get a feature_names mismatch error when I run it. The features are all numerical features and there are no missing values.
cols_to_use = ['Product…
Nekojell
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Comparing the predicted class for each instance of test data from different models
My test set data contains about 50,000 instances. I trained different machine learning models. Now I want to do some comparison to see for example if for every instance x_i that model A predicted as 0, models B and C also predicted that instance as…
user12587364
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Supervised Neural Networks
I am reading a lot of articles about neural networks and I found very different information. I understand that the supervised neural network can be also regression and classification. In both cases I can use the sigmoid function but what is the…
Inuraghe
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Would the division of classes into subclasses increase the predictive accuracy of image classification?
If images in a class differ in image classification, should the class be further subdivided into subclasses in which the images are more similar, or is that not necessary because different features can be learned in image classification?
For…
Anne Maier
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Machine Learning approach for automating document filing into the correct folder
I am wondering if anyone has any ideas to the correct approach and suitable algorithms for the below scenario:
There a thousands of distinct documents each with their own categorical encoding. These documents arrive into the system and need to be…
bjg90
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Learning algorithm to implement XOR gate
I know we can't use perceptron learning algorithm to implement XOR gate because it is a lineraly inseparable problem. So my question is which learning algorithm and which neural network can we use to implement XOR gate? I tried using Delta rule, but…
Vipul Tyagi
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Which supervised machine learning classification method suits for randomly spread classes?
If classes are randomly spread or it is having more noise, which type of supervised ML classification model will give better results, and why?
Amit
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Dataset Language identification
I am working on a text classification problem with a multilingual dataset. I would like to know how the languages are distributed in my dataset and what languages are these. The number of languages might be approximately 8-12. I am considering this…
yolo25
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Did I screw up my entire data science homework assignment by standardizing my data?
Professor wanted us to run some 10 fold cross validation on a data set to get the lowest RMSE and use the coefficients of that to make a function that takes in parameters and predicts and returns a "Fitness Factor" Score which ranges between 25-75.…
alexstrasza
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