Questions tagged [binary-classification]

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Gradient boosting algorithm implemented in LightGBM

I'm currently reading the documentation of LightGBM and I'm wondering which gradient boosting algorithm is exactly implemented there if choose boosting parameter as "gbdt" or "dart?&...
Julian's user avatar
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Does a random classifier have a diagonal ROC (received operator characteristic) curve even when the data is biased toward negatives?

About 9% of the US population have a diabetes diagnosis. So a binary random classifier that just guesses 50% positive and 50% negative would likely be incorrect when it guesses positive (leading to ...
joseville's user avatar
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Pycaret cross validation scores are way lower than unseen test set scores

How come the cross-validation model scores are much lower than the model scores on an unseen dataset? ...
yoavf's user avatar
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1 vote
1 answer
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How to balance labeled datas and then carry out execution with a certain ratio?

I'm building a binary classification model using a neural network, with python and the libraries tensorflow and keras. For that I have an unequal amount of labeled data: Around 2'000'000 labeled with <...
user155518's user avatar
3 votes
2 answers
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ROC curve for a perfect model, why is AUC 1.0?

According to this article, The ROC curve for a perfect model would go straight up the TPR axis on the left and then across the FPR axis at the top. Since the plot area for the curve measures 1x1, the ...
T. Webster's user avatar
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Empty Confusion Matrix and Zero Precision/F-score

Could you please say why I'm getting this warning while doing a binary classification using Artificial Neural Networks? The data are colored images. ...
Totoro's user avatar
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1 answer
54 views

Correct way to take a subset of a dataset?

I am attempting a binary classification problem (using Weka). My dataset has 100,000 rows, 14 attributes (1 output variable). It takes already too long just to open the dataset in excel so I just know ...
FlexMcMurphy's user avatar
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30 views

Model can not fit to 8 datapoints

I have 10 groups of biological experiments, all of size 100. I want to estimate experimental performance (success rate) of each groups of experiments, but have only ran experiments in two groups. My ...
TheNumber23's user avatar
1 vote
1 answer
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How do I best approach a multiple-target binary classification in Tensorflow/Keras?

I currently have eight features which are either categorical or continuous variables. My targets are many (~1000) binary variables. So far I have attempted skmultilearn and sklearn.multioutput. I ...
FoolsGold1997's user avatar
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Why is my Histogram Gradient Boosting Classifier model still producing type II error? How can I reduce the type II error?

Type 2 error and how to hypertune or feature engineer a solution for it I trial and tested different techniques and kept the structure which made the most sense to me. But still my model confusion ...
bitebytebit's user avatar
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2 answers
36 views

Binary classification using RNN not going beyond 50% accuracy

I am trying to find out the reason behind why my RNN network won't go beyond 50% for binary classification. My input data is of the shape: ...
Prabhjot Singh Rai's user avatar
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Competition test set performance much lower than validation set

We are a team of 3 participating in a university competition for a deep learning course. The competition involves a binary image classification task where we have to predict leaf diseases on a (5200, ...
Fiorenzo Fiorenzi's user avatar
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Logistic regression with E-net regularization produces different set of weights with each run

I am currently trying to make a model to classify brain tumor patients by incidence of epilepsy using a combination of variables extracted from clinical records, and radiomics features from segmented ...
reuben george's user avatar
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1 answer
203 views

Training ResNet50 model for binary classification

I want to use ResNet50 model to perform binary classification on a dataset spectrogram dataset. In order to do that I had to make a couple of modifications to the model's architecture: Modified the ...
leapofFaith's user avatar
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Binary classification using xgboost

Why when adding new features in my ADS for a binary classification using XGBOOST my score and uplift has decreased ? What is the best way to treate categorical features or other features in order that ...
Warda_IDRIS's user avatar
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1 answer
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Different accuracy scores with sklearn roc_auc_score on same model using sklearn.metrics

Why do these below lines give different outputs while the input is the same? I need to report these results in paper, but I am unsure which is better and why. ...
Adnan Ali's user avatar
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3 answers
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Reduce false positives having imbalanced data

I'm using a DNN-48 having the following scenario: Features: 8 (48 at the end because I generate conditional sequences of 6 elements each) Classes: Y=0 (90%), Y=1 (10%) Precision and recall are good ...
Gabriel's user avatar
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Decision making in a binary classification problem

Consider a two-dimensional feature space in which the line $\mathbf{w}.\mathbf{x} + b = 0$, where $ \mathbf{w},\mathbf{x} \in \mathbb{R}^ 2 $ and $b \in \mathbb{R}$, separates linearly separable data ...
Tirthankar's user avatar
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Predicting Year-End Outcome from Monthly (and Annual) Data

I have data on customers' usage of various product features over time. Each month, a customer can choose to use a feature or not. I want to create a live system that produces the probability of a user ...
pyassign67's user avatar
2 votes
1 answer
37 views

Changing model architecture doesn't impact results

I am currently learning binary classification. The problem is classifying positive and negative movie reviews. The dataset is 25,000 reviews with each review represented by 10,000 of the most used ...
Omer Mualem's user avatar
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2 answers
58 views

Can you obtain classification thresholds for specific features in a Random Forest?

Say I've created a random forest model for binary-classification prediction target of either "Pass" or "Fail" for a group of students based upon numerical features "Hours ...
Petunia's user avatar
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2 answers
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Is this an unusual distribution for a sigmoid output from a neural network?

Shown here is the histogram of around 130K predictions of my deep neural network that is classifying some financial data. This is on the dev set but a similar distribution is also seen on the train ...
BYZZav's user avatar
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Binary classification metrics for one-hot label encoding in Tensorflow

I run a binary classification using different CNN versions in Tensorflow. When I label samples from each class using 0 and 1, I select a sigmoid output in the last layer of the CNN, like ...
GKH's user avatar
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BCE loss stuck at 0.693 in the beginnng of training and then started to decrease, why?

I'm using a Transformer encoder with a binary cross entropy loss for CTR prediction. The training batch loss is at around 0.693 constantly for the beginning several thousand steps (batches). I'm using ...
CyberPlayerOne's user avatar
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1 answer
419 views

Torchmetrics Binary Accuracy and Multiclass Accuracy don't match

in my program I have the problem that for a 2-class classification problem my multiclass accuracy and binary class accuracy don't match. I have generated a very small sample example where you can see ...
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1 answer
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Classification Problematics : Feature Number Variance & Feature Repetition

I have a harsh case study (in my mind). The problem is I need make binary classification on Quality of Service (good or bad). I have a feedback on quality on groups of devices belonging to company. I ...
secuf's user avatar
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1 vote
1 answer
241 views

precision and recall is zero

Why my model shows metrics like this? While my model was training recall and precision was equal to zero? I trying to do binary classification of mushrooms [edible, poisonous]. I have CNN model with ...
User Name's user avatar
0 votes
3 answers
201 views

How to properly do a k-fold cross validation?

I am trying to solve binary classification problem using deep neural networks. I want to compare different approaches (model architectures) and I have no hyperparameters which I want to tune. So my ...
dmasny's user avatar
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0 answers
12 views

Comparing probability models for alignment

I have a probability model which predicts a probability for a binary classification problem. I am interested in how well the predicted probability aligns with the true probability. For instance, you ...
Moss Richardson's user avatar
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1 answer
147 views

How to reduce the false positives to improve the models performance?

I am currently building a binary classification model to predict order return rates. I used the GradientBoostingClassifier for training the model and also performed hyperparameter tuning using ...
Kedharnath Kb's user avatar
0 votes
1 answer
72 views

Single model or multiple models for predicting at each level in a multi-level classification problem

Given a flat structured data with features that can be considered hierarchical, where each feature is at a different level (e.g., Brand at the top level, Product, Color, and Size at different levels), ...
Kedharnath Kb's user avatar
1 vote
0 answers
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How to calculate threshold values for a simple binary classification model

Consider a binary classification problem with two features. Let's assume that the higher the value of each feature the more likely a datapoint is to be positively classified. Additionally assume we ...
Daniel Wyatt's user avatar
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1 answer
216 views

Why does Logistic Regression perform better than machine learning models in clinical prediction studies

I am developing binary classification models to predict a medical condition in my dataset. My results show that both Logistic Regression and Linear SVM consistently outperformed other ML algorithms (...
sums22's user avatar
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0 answers
190 views

Weighting and loss function for multi-dimensional output on ECG neural network in Tensorflow

I am working on a DNN that is training on ecg data with a shape of [None,1,2500] and output shape of [None,12,19] where 19 is a ...
ekg-display's user avatar
1 vote
1 answer
35 views

How to bias a neural network towards one category in binary classification?

I have a basic sequential neural network built with TensorFlow. ...
Chandler Kenworthy's user avatar
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1 answer
119 views

Decision boundary of an neural network

Starting with a). For the first unit: 0 * x1 + 1 * x2 + 1 > 0 (0, because the threshold is 0) which is the same as x2+1 > 0. For the second unit: x1 * 1 + x2 * 0 + 1 > 0 (0, because the ...
kim120's user avatar
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0 votes
1 answer
503 views

Is deep learning high initial validation accuracy a sign of problem?

I have a image classification model with 8400 images of class A and 1800 images of class B. I have used validation_split=0.2 with subsets of ...
Amin Alaee's user avatar
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0 answers
146 views

Classifier calibration leading to worse outcome

I am trying to calibrate some classifiers to output more accurate probabilities. For this, I am using a sigmoid regression as implemented in ...
C.S.'s user avatar
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1 vote
1 answer
119 views

Probability distribution of probabilities

We can get the prediction probabilities of a binary classifier from sklearn's API using the predict_proba method. Is it reasonable to expect that the shape of a histogram plotted for the prediction ...
zebinx's user avatar
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0 votes
1 answer
320 views

VC-dimension of the class of hypotheses that assign label $1$ to exactly $k$ points of some finite domain $\mathcal{X}$

Let $\mathcal{X}$ be a finite domain and $k$ a number such that $k\leq|\mathcal{X}|$. Consider the hypothesis class $\mathcal{H}:=\big\{h:|\{\mathbf{x}\in\mathcal{X}:h(\mathbf{x})=1\}|=k\bigr\}$; that ...
VK88's user avatar
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0 answers
38 views

Binary Classification: My model classfies most data (95%+) as label 1

I am working with ECGs and trying to use a CNN model to perform binary classification. The goal is to classify 30s ECGs to detect a specific disease. I am using CNN and converting ECGs to images (...
makala's user avatar
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0 votes
1 answer
88 views

Quasi complete separation problem

I have some question related to quasi complete seperation problem on logistic regression algorithm. So i run the model to predict credit risk and turns out it gave me good prediction score (AUC around ...
Jovian Aditya's user avatar
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0 answers
270 views

Custom loss function for binary classificatio in Keras gets error: No gradients provided for any variable

I have a binary classification problem. However, I don't really care about fp and fn values. What I want to achieve is that the <...
Farzad's user avatar
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3 votes
1 answer
72 views

What does precision-recall curve and ROC curve tell us abouth threshold invariance

Consider a binary classification problem. Intuitively, a value for the area under the curve (for both curves) very close to 1, shows that the curve is almost L-shaped. Thus, this means that the value ...
liakoyras's user avatar
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0 votes
1 answer
59 views

Input Tensor Shape for CNN Binary Classification of Time Series Data

I want to predict whether a machine will fail based on the most recent set of measurements taken by on-board sensors. I have several dozen machines, each with a sensor that takes a measurement at ...
Rory Majule's user avatar
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0 answers
16 views

ANN Input vector representing a network of contests's outcomes between thousands of individuals?

Let's say I have 1000 participants within a tournament, each of the participants having a single ID. One instance of this tournament is a 1 vs 1 contest when one wins and the other loses. Now let's ...
Stak33's user avatar
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0 votes
1 answer
215 views

Mixed effects models for a classification task on panel data

I have a problem where I need to make predictions for a binary target $y$ given a set of features $X$ where $X$ is naturally nested in the form of repeated measurements. The data is meant to describe ...
bmasri's user avatar
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1 vote
3 answers
156 views

ROC Curve for model validation

Is there a general approach that the ROC curve can be used for to validate a model? My understanding is that we can use it to compare different threshold values to determine the best, or even see how ...
user143064's user avatar
1 vote
2 answers
64 views

Classification of data points using vertical lines through visualisations

I am currently doing my master's thesis and at the end of finishing it, but there are some questions raised by my supervisor. I have answered most of the questions, but only one question is remaining ...
user1791442's user avatar
0 votes
1 answer
37 views

"Inverted" correlation of the amount of the loan and the probability of default

My task is to make a machine learning model for predicting the probability of default when taking a loan (binary classification). But I also want to predict the loan amount. Something like: if the ...
Andrew's user avatar
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