Questions tagged [supervised-learning]
Supervised learning is a type of machine learning algorithm that learns a mapping function y = f(x) between input variables (x) and output variables (y). The two most common supervised learning tasks are classification and regression.
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Does Including Contamination Turn Isolation Forest into Supervised?
In unsupervised anomaly detection, does including the contamination percentage turn isolation forest into supervised instead of unsupervised when I fit the data after?
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How to Predict Remaining Lifetime or Replacement Probability of Machine Parts?
I am diluting and abstracting away some details to protect the client, but the basic idea like this.
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An authorised vehicle service centre run by a company, something like Audi, where vehicles ...
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Generating transaction data for a dataset to train on
My project is to predict what payment option a customer might use depending on various factors on a checkout screen.
For example here are some of the fields I would have
Variables : User_Location ...
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balancing and imbalancing in supervised anomaly detection probelm
I am dealing with a supervised anomaly detection problem, where I have labels with 0 for normal and 1 for abnormal. The default distribution of the dataset is highly imbalanced with a ratio of 96:4 ...
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Converting multiple binomial logits to multinomial
I am faced with a image classification problem with 3 classes. My existing network consists of 3 'branches' each corresponding to one of the classes. Each of these branch outputs a binomial logit ...
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Measures of efficacy for one classification models on the same data set with different numbers of classes?
I am currently doing a university project in supervised learning. The variable to be predicted varies across the integers [0,100] and my supervisor suggested to split this range into different classes ...
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How do I determine syndicate and collusion indication with clustering and network analysis on a large unlabeled user transaction data?
How do I determine syndicate and collusion indication with clustering and network analysis on a large unlabeled user transaction data?
So far, I've only been training with labeled data on fraud-...
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How does ROC work with SVM?
Could someone please explain how ROC works with SVM?
Specifically i'm using RocCurveDisplay.from_predictions(y_test, y_pred, ax=ax[1]) which works fine.
Since the ...
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unsupervised clustering followed by modeling each cluster to create a mixed model
I am curious if this is an advisable approach. I am not applying this approach and am only interested in the theory of it.
let's say you have some set of features X and target Y.
X can account for ...
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How to deal with a dataset in which categorical features have one value for specific class?
I have a multiclass problem and for the class equal to 2 in the target I have some categorical columns with just one value.
For instance, is like for the observatuons with the target equal to 2, the ...
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How should I use ML to extract the entries from a dictionary?
A question about methodology
I know that methodology questions are not welcome on the Stack Overflow site, but I don't know if they are acceptable here. If they are not, I apologize.
Description of ...
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Why does data science see class imbalance as a problem for supervised learning when statistics does not?
Why does data science see class imbalance as a problem in supervised learning when statistics says it is not?
Data science seems to seem class imbalance as problematic and needing special techniques ...
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Improving performance of anomaly detection using dataset?
I am leveraging an isolation forest model from the scikit-learn library for anomaly detection in a time series dataset where each point in the dataset is a data frame. However, I possess additional ...
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Counting Number of Holes in an Image of Cheese
I've been assigned a project that involves writing a script to detect the number of holes in an image of cheese. My background in AI is quite limited, so I was wondering if anyone could give me a good ...
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Looking for a way to train a model to learn parameters for clustering
I have 5000 docs, each is a review. For each review, i'm plotting the sentences in a semantic dimension.
Now, I'm applying clustering to these points for each review. The success of my model depends ...
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