Questions tagged [classification]

An instance of supervised learning that identifies the category or categories which a new instance of dataset belongs.

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12 views

how to get the classe names in an image classifer after predection?

I made an image classifier of 80 classes of handwritten numbers then I tested my model and it worked pretty fine, the only problem that I have now is the display of the correct names of these classes. ...
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How to formulate my data for an LSTM, classification problem?

I have several input data that I have ordered chronologically (temperature, wind, etc.) and which cause me to output the output value (1or0). I have a csv file which contains chronologically ordered ...
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improving accuracy of logistic model

I am trying to reproduce results from one paper, where authors minimized the following loss function \begin{align} \min_{w \in R^d} \frac{1}{n} \sum_{i \in [n]} log(1 + exp(-y_ix_i^Tw))+\frac{\lambda}{...
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Formula to calculate confidence value in Adaboost

I am coding an AdaBoostClassifier with the two class variant of SAMME algorithm. Here is the code. def I(flag): return 1 if flag else 0 ...
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31 views

Recursive Feature Elimination (RFE) with Logistic Regression and little correlation between the features and the target (SKLearn)

I have little experience in the field of Machine Learning, so I apologise in advance for my ignorance and lack of intuitions. I'm trying to build a classifying algorithm to identify if a subject is ...
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How to make a classification problem into a regression problem?

I have data describing genes which each get 1 of 4 labels, I use this to train models to predict/label other unlabelled genes. I have a huge class imbalance with 10k genes in 1 label and 50-100 genes ...
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How do you choose the min and max for the min-max normalization on a histogram classifier?

Please let me know what to do when there is a value in the testing set is bigger than the max value used to min-max normalize the training set building a histogram classifier. Do I go back and change ...
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What is the best approach for send time optimization? [closed]

I could no find a lot information about how the companies doabout send time optimization, either for push notifications or email campaigs. having historical data about clicks and sends what would be ...
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Log normal Distribution

https://www.kaggle.com/nowke9/ipldata After downloading this dataset, I wrote the following commands to load and display the dataset. import math import numpy as np import pandas as pd from scipy ...
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Can you combine two xgboost models into one?

If you have built two different xgbost models, with say 100 trees each, is it possible to combine into an xgboost model with 200 trees?
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Decreasing n_estimators is increasing accuracy in AdaBoost?

I was exploring the AdaBoost classifier in sklearn. This is the plot of the dataset. (X,Y are the predictor columns and the color is the label) As you can see there are exactly 16 points in either ...
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Text data distributions comparison

I would like to know what is the best method to compare the different text data distributions. I am working on text classification. I built a model using the old dataset. Now, I would like to know, ...
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None of the known overfitting prevention techniques works for me, according to learning curves

I am working on HTRU2 dataset to evaluate classification models. Even though I obtain good results in terms of accuracy-MSE: I have an overfitting problem according to the learning curves below. In ...
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Characterizing nonlinear pattern inside the noise from the scatter plot

I have the following scatter plot. The following scatter plot example consists of 1) two traces of curve and 2) background noise as you can easily characterize by just looking at them. In this case, I ...
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What is the current best state of the art algorithm for graph embedding of directed weighted graphs for binary classification?

Sorry if this is a newbee question, I'm not an expert in data science, so this is the problem : We have a directed and weighted graph, which higher or lower weight values does not imply the ...
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Do I use the mean vector from my training set to center my testing set when dimension reducing for classification?

Please let me know if this is the right place to ask this (or if any of my tags are wrong) or if I need to write this any differently. Do I use the mean vector from my training set to center my ...
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How should I clean the columns of the dataset “Application-Layer DDoS Dataset” from Kaggle?

I'm trying to get the right kind of data to build my model. I'm using TensorFlow's DNN classifier for this model. The dataset I'm using is Application-Layer DDoS Dataset from Kaggle. I've encoded the ...
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LOGICS: GAN with image as input instead of a noise vector

i am having an idea for a single-class classifier. I don't know if this is a logical "short circuit", though. The idea is the following: Instead of a noise vector, i use a "noise-image" as input for ...
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How is the weight matrix set and its dimension in CNN

I am trying to calculate the output size of each layer and the number of parameters for 3 class classification using CNN. I have calculated till the final maxpooling layer and would really appreciate ...
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How to impute missing values for hour of day?

I have a dataset containing a certain amount of bookings, no shows and cancellations. We assume that a cancellation less than 2 days is the same as a no show (since you did not have the time to ...
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Is it better to have higher train accuracy with lower test accuracy or higher test accuracy with lower train accuracy?

The results from my RandomForest model with 5 max features are as follows: 84% train accuracy 76% test accuracy The results with 10 max features: ...
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Confusion matrix and ROC AUC curves are not in sync

I created a classification model with three target classes and created a confusion matrix to measure the accuracy, here is the matrix code ...
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How to deal with broad and narrow variance within classes in classification tasks

Let's say I'm doing an animal image classification task (it doesn't have to be image classification - this is just my example), and the training and test data is balanced across classes. The classes ...
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Since is not possible test all the possible combination, what is the correct procedure to follow on building Machine Learning?

Sorry, I'm a little confused and this is a general question. How can I be sure that the procedure that I am following is the correct one? Following the steps for building a machine learning model, we ...
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why does adding an LDA document vector with a word2vec word vector work well in LDA2vec?

In LDA the document weight vector represents the "weights" of each topic in the document. I think it's also valid to say, each row in the document vector corresponds to a word in the document, the ...
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HR Machine Learning: Treating/ Standardizing Part Time Employee Sums To Their Full Time Equivalents in Attrition Modeling

My data set consists of a subset of employees. Each employee has general HR information (typical standard hours, department, site, etc) along with punch card data which gives a clear picture of the ...
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ValueError: “The estimator should be a classifier”

I am adapting sklearn-extension ELMClassifier to be accepted as base_estimator to both VotingClassifier and AdaboostClassifier. ...
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Generate a balanced batch with ImageDataGenerator() and flow_from_directory()

Hi I am new to python and deep learning. I am doing a multiclass classification. My 3-classes dataset is imbalanced, the classes take about 50%, 40%, and 20%. I am trying to generate mini batches with ...
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Multiclassification problem [closed]

I was wondering what happens when an image not in the training set is provided to the model in a multiclassification problem? Does it just classify something which is close to this image?
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Dissecting performance issues with Random Forest

My task is to identify potential situation for trading and determine whether a candidate is going to succeed or not. I have a system in place to identify candidates, but there is a high rate of false ...
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Discrimination vs Calibration - Machine Learning Models

I came across a new term called Calibration while reading about prediction models. Can you please help me understand how different it is from ...
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35 views

can I use t-sne or PCA to reduce number of classes?

I wanted to know if I can use t-sne or PCA to reduce the number of classes depending on the similarity between them. For example, if I have 100 classes of 100 different animals and would like to put ...
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I want to know which machine learning algorithms can be used for trajectory classifications?

I am working on project for clustering of air objects based on their trajectories. Like I want to train a model on dataset of different flying object's trajectories so later I can predict what type of ...
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How to apply model to training data to identify mislabeled observations?

I have a list of people, attributes about those people (height, weight, blood pressure, etc.), and a binary target variable called has_heart_issues. This data ...
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Classification with a lot of the classes

I’m trying to make model which will classify text into about 500 different classes. I think that I have to customize architecture of the Pooling Classifier which looks now like this: ...
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Is test data needed on model with no hyper-parameter

I am doing classification using Linear Discriminant Analysis (LDA), which has no hyper-parameters. I am aware the difference between validation and test set, i.e. validation is used for hyper-...
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K-Nearest Neighbour Classifier Best K Value

I created a KNeighborsClassifier for my dataset adjusting the k hyper-parameter (the number of neighbours) in a for loop. The k value was between 1 and 20. The ...
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Probabilistic gold standard vs Deterministic gold standard

I understand that we say something as a gold standard when it involves human intervention/judgement/review. But can someone help me understand what's the difference between probabilistic gold ...
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how can i use twitter API to extract terms or words in Arabic language without coding

I get the approval from twitter developers to access the data from twitter to collect data set in Arabic but I don't know how can I utilize without using code I need to extract data directly by ...
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Serializing a trained classification model into a set of actionable insights

I'm looking for ways to convert a trained classification model into a list of insights based on the resulting parameters of the model. To make an example, let's assume we trained a decision tree to ...
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1answer
51 views

Reformulating the maximal margin classifier optimization problem

Ok, so I've been trying to read up on how SVM's work and started with maximal margin classifiers. At page $132$ in ESL (Elements of Statistical Learning) the authors "reformulates" the optimization ...
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Cross-entropy loss colloquially

I have just made an MNIST classifier from a tutorial. It has 1 layer, no hidden layers. It uses PyTorch's nn.CrossEntropyLoss as a loss function. Plotting my losses ...
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1answer
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I have 3 graphs of a binary Logistic Regression that I want to understand better what is happening and learn of a strategy to make the model better

My problem is the following: I have a binary Logistic Regression model with a very imbalanced dataset that outputs the percentage of the prediction. As can be seen in the images, as the threshold is ...
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1answer
25 views

DL model to assess quality of image

I have an idea but I am not certain that it can be modeled in a DL architecture. Let's say we have images of different qualities based on color patterns and their assessment as labels in a range from ...
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Is it reasonable to use the output of the sigmoid function as the win rate prediction?

I'm working on a project which is predicting the win rate of one team or one person. (could be any kind of sports like baseball, basketball or e-sport games) The data I have is more like a ...
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3answers
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Why does my KNeighborsClassifier graph look like this?

I'm new to data science/ml and working on using the sklearn libraries to classify data. I'm currently using the KNeighborsClassifier with 5 fold cross validation whilst tweaking the k value but its ...
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Custom learner for sklearn AdaboostClassifier

I'd like to use scikit-learn AdaboostClassifier differently from the original proposal: 1) I want to mix different types of weak-learners in one Adaboost ...
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1answer
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xgboost classifier predicted negative probabilities

I'm using XGBoost for a binary classification problem. There is no negative label, only 1 and 0. I tunned the hyperparameters using Bayesian optimization then tried to train the final model with the ...
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Using Neural Networks on images to predict successful vs unsuccessful trades

The context for the problem is day trading: identifying the moment when one can buy units of a stock and then wait for them to grow in value before selling them at the new price. Currently I have a ...
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Index confusion after splitting, normalizing and oversampling the data set

I am working on a data set with 16,259 samples with class label 0 and 1,639 samples with class label 1. In order to balance the data set, I am applying oversampling (after normalization). The problem ...

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