Questions tagged [scikit-learn]
For questions related to the Python's package scikit-learn (or sklearn).
29
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How to make a RandomForestRegressor learn to differentiatie similar inputs with different outputs?
I'm working on a regression task with Sklearn RandomForestRegressor and I'm having some trouble distinguishing between two similar data with very different expected outputs. For example, each pair of ...
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Confusion about the code for choosing "stumps" in Adaboost algorithm
(I actually asked the following question on Stack Overflow and Cross Validated Exchange for more than a month:
https://stackoverflow.com/questions/76842431/confusion-about-the-code-for-choosing-...
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I'm trying to understand the use model for different Python libraries
I'm new to ML/AI field, and after completing several free university courses from MIT OpenCourseWare and Harvard CS50, I've gained some familiarity with the theoretical foundations of Artificial ...
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cross_val_score of sklearn and LinearRegression scoring method
cross_val_score (https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_score.html) uses the estimator’s default scorer (if available) and LinearRgression (the estimator I ...
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110
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Can I implement a sklearn model inside a Pytorch nn.Module? [closed]
I am making a custom Pytorch model that at some point, clusters a latent space that was created by another, previous routine of the model (Autoencoder).
In a bit more detail, my model is a regular ...
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31
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How to convert my test data in the same dimensionality as my train data
I have trained a VAE with jpg images. My latent space dimension has 768 features and when plotting the latent space it looks like this:
However, when I use the scikit learn tool LDA (Linear ...
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44
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Using ML to uncover procedural logic
The game Elite Dangerous has a proceduraly generated galaxy of some 400 billion star systems.
Each star system in the game can be uniquely identified bu a 64bit number (id64) which is used as a seed ...
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202
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Why does KNN Model return 99% accuracy on dataset with default parameters? [closed]
I am building a model that predicts if a user will like a stock or not based on different features, such as Market Cap, Current Ratio, Sector, Trailing PE, etc. I am going to implement this model in a ...
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55
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How to evaluate binary classifier on imbalanced dataset?
I have trained a Decision Tree model on an imbalanced dataset. I got the following results for the test set from the sklearn and imblearn classification reports (attached below). Moreover, the other ...
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Unexpected behaviour on using class weights in loss
I’m working on a classification problem (500 classes). My NN has 3 fully connected layers, followed by an LSTM layer. I use nn.CrossEntropyLoss() as my loss function. To tackle the problem of class ...
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146
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How to interpret binary classification metrics on an imbalanced data set?
I have an imbalanced dataset on intrusion detection. I have (attack class) 3668045 samples and (benign class) 477 samples. I made a 70:30 Train test split. My problem is to predict whether the given ...
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444
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Why does GridSearchCV model give worse results despite same parameters used with base model
I am trying to make prediction using random forest regression and then utilize GridSearchCV to tune hyperparameters(just 'n_estimators'). However results of GridSearchCV are worse than base model. ...
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167
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Why does sklearn perceptron converge for linearly inseparable data points?
I learned that the perceptron algorithm only converges if the dataset is linearly separable. I am implementing this algorithm using scikit learn.
The blue and orange points are from the training set, ...
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1
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44
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'Advancing' basic models
Good morning.
I am a student running a project using medical data, predicting if the patient will or won't get a disease. The data has about 50k cases and 70 features.
I proposed to train 5 models- ...
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2
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Is sklearn using both a threshold and a bias term? [closed]
Reading this Can a neuron have both a bias and a threshold? has confused me, as it appears to be more common to use a threshold of 0 when using bias. But reading this https://stackoverflow.com/...
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187
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How can I interpret the value returned by score(X) method of sklearn.neighbors.KernelDensity?
For sklearn.neighbors.KernelDensity, its score(X) method according to the sklearn KDE documentation says:
Compute the log-...
- 225
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354
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How to make a proper approximation of Sine function with Neural Networks?
TL;DR;
How to build a neural network that properly approximates the sine function with different ranges?
Context and Question:
From this question I decided to use the Sergey's answer, however I used a ...
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110
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What is the best machine learning algorithm for clustering dots based on coordinates $(x,y)$ with consideration of weight of the points?
I'm looking for a machine learning algorithm for clustering points based on their coordinates. Furthermore, I want to take into consideration the weights of each point. Suppose there is a weight in ...
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1
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115
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Do I need to tune the hyper-parameters or more data if SVR model performs poorly?
I am using non-linear data to SVR and have tried tuning the hyperparameters and still have a poor model performance. Do I need more data or format the data for more suitable results?
I get similar ...
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30
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How matrix factorization helps with recommendations when it converges to the initial user-items matrix?
We can say that matrix factorization of a matrix $R$, in general, is finding two matrices $P$ and $Q$ such that $R \approx P.Q^{T}$ with some constraints on $P$ and $Q$. Looking at some matrix ...
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470
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When computing the ROC-AUC score for multi-class classification problems, when should we use One-vs-Rest and One-vs-One?
The sklearn's documentation of the method roc_auc_score states that the parameter multi_class can take the value ...
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Why isn't my decision tree classifier able to solve the XOR problem properly?
I was trying to solve an XOR problem, and the dataset seems like the one in the image.
I plotted the tree and got this result:
As I understand, the tree should have depth 2 and four leaves. The ...
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262
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Train a model using a multi-column text-filled excel sheet
I have an excel sheet filled with my own personal appreciations of movies I've watched, and I want to use it to train an AI model so that it can predict if I'll like a specific movie or not, based on ...
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Suitable deep learning algorithms for spatial / geometric data
I have a task of classifying spatial data from a geographic information system. More precisely, I need a way to filter out unnecessary line segments from the CAD system before loading into the GIS (...
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129
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Interpretation of feature selection based on the model
The description of feature selection based on a random forest uses trees without pruning.
Do I need to use tree pruning?
The thing is, if I don't cut the trees, the forest will retrain.
Below in the ...
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How can I split the data into training and validation sets such that entries with a certain value are kept together?
I have the following kind of data frame. These are just example:
A 1 Normal
A 2 Normal
A 3 Stress
B 1 Normal
B 2 Stress
B 3 Stress
C 1 Normal
C 2 Normal
C 3 Normal
...
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Can ML be used to curve fit data based on dataset of example fits?
Say I have x,y data connected by a function with some additional parameters (a,b,c):
$$ y = f(x ; a, b, c) $$
Now given a set of data points (x and y) I want to determine a,b,c. If I know the model ...
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Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?
I am using raw data set with 4 feature variables (Total Cholesterol, Systolic Blood Pressure, Diastolic Blood Pressure, and Cigraeette count) to do a Binominal Classification (find stroke likelihood) ...
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How can I use gradient boosting with multiple features?
I'm trying to use gradient boosting and I'm using sklearn's GradientBoostingClassifier class.
My problem is that I'm having a data frame with 5 columns and I want ...
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