Questions tagged [scikit-learn]

For questions related to the Python's package scikit-learn (or sklearn).

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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 ...
0 votes
1 answer
27 views

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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1 vote
1 answer
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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 ...
0 votes
2 answers
97 views

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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1 answer
46 views

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. ...
1 vote
1 answer
60 views

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, ...
0 votes
1 answer
40 views

'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- ...
0 votes
2 answers
84 views

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/...
1 vote
1 answer
68 views

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-...
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0 votes
1 answer
218 views

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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0 answers
109 views

Is this the correct method for how to implement a stratified K fold with grid search SVC?

I'm writing a support vector classifier for a binary class using some toy data. This is the code: ...
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0 answers
24 views

Is it possible that k-means generates a cluster with no points in it, if the initial centroid is not properly set and no of cluster is large?

Is it possible that sklearn's k-means algorithm will generate a cluster that has no points at all, given that the number of k is large and the initial centroid is just random? Furthermore, will k-...
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0 answers
69 views

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 ...
0 votes
0 answers
7 views

Predicting single floats based on set of 2 feature arrays each of 100 values

I am trying to predict audio to video desynchronization based on ser od two arrays of lenght 100 which consist of coresponding audio and video samples. The problem is that my labels are single floats (...
0 votes
1 answer
81 views

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 ...
2 votes
0 answers
26 views

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 ...
4 votes
0 answers
398 views

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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3 votes
1 answer
400 views

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 ...
0 votes
1 answer
153 views

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 ...
2 votes
0 answers
65 views

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 (...
1 vote
1 answer
121 views

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 ...
1 vote
0 answers
63 views

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 ...
4 votes
2 answers
2k views

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 ...
2 votes
1 answer
72 views

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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1 vote
0 answers
72 views

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 ...