Questions tagged [binary-classification]

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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
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1 answer
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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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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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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 ...
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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 ...
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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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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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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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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
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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 ...
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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
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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
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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
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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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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 (...
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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
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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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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 ...
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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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Understanding perceptron learning algorithm

I was revisiting perceptron learning algorithm. The wikipedia page gives the algorithm as follows: Initialize the weights to 0 or a small random value. For each example $j$ in our training set $D$, ...
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High dimensionality one class input

I am currently doing research on anomaly detection and currently I am facing the following problem: My input data has only one label (anomalies) and the associated data has a very high dimension and ...
much_data_many_mem's user avatar
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Approaching multiple records for one observation; radiomics of 2D slices of a 3D object

Background I am trying to create a model that can predict Type 2 diabetes in a patient based on MRI scans of their thigh muscle. Previous literature has shown that fat deposition in the muscle of ...
Saminy Creed's user avatar
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How to give a column a special weight for any algorithm? (binary option)

I'm dealing with binary option, I'm making a classification model using xgboost, my idea is to predict the posterior candle color by using some data of the 20 previous candles so I made a dataset on ...
Davi Américo's user avatar
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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 ...
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1 answer
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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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1 answer
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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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How to get the top feature contributors for the differnt classes in the classifiction model?

In classification model , we build models with binary/multi class responses. Is there way to get the top features contributing positively,negatively to each of the classes.( i.e top features helping ...
Scope's user avatar
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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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Using features extracted from CNN and handcrafted features to perform classification

I have a question in regards to merging features extracted from CNN and handcrafted features. I have been reading this paper https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002895/#B33-sensors-22-02467 ...
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How to quickly create hundreds of binary variables from continuous

I have 342 continuous variables for proteins for which I would like to create a binary variable for a predetermined cut-off. E.g., if the continuous variable "HsCD00076570" has a value > ...
Jack Murphy's user avatar
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1 answer
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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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Why validation loss curve not decreasing of my ResNet50 model while training loss decresing? How I can improve without using transfer learning?

I am trying to understand my model by diagnosing the learning curve and how I can improve it. I aim to implement a deep-learning architecture (ResNet50) using a small dataset for binary classification ...
Mohammed Nurul Islam's user avatar
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229 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
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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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1 answer
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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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Is it correct to generate similar rows by reducing the time-frame of an instance?

I'm participating in a People Analytics project with a small historic dataset that includes event variables. The aim is to predict employee's attrition. I have variables like area, dept., company, etc....
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Can a Binary classifier be used to understand the relationship between categorical data and multivariable time series data?

I'm looking for peoples advice and opinions on a certain analysis approach I'm thinking of doing for my experiment. Experiment Effectively I flash a light into a mouse's eyes and record the activity ...
Saxon Berry's user avatar
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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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Understanding Cost-sensitive Decision Trees Behaviour

I have a binary classification problem with imbalanced data and am attempting to use cost-sensitive learning to handle the imbalance. I have used LogisticRegression, LinearSVC, SVC and DecisionTree ...
sums22's user avatar
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1 answer
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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
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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
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0 answers
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What are the best CNNs for synthetic images?

I am performing binary classification on an image dataset that comprises of synthetic images, i.e. pixelated images of random colors and patterns with no objects in them (like cats, flowers etc.). I ...
Amadeo Amadei's user avatar
1 vote
2 answers
49 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
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1 answer
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"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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1 answer
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Good models for predicting whether a customer would make a purchase given details like age, gender, ethnicity, salary, etc?

I have around 30,000 data points and for those data points I have some numerical fields like customer_age, ...
Tom's user avatar
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Worse performance on positive class - probability prediction with lightgbm

I would like to predict probabilities in a binary class setting. I want to use the probabilities directly to make decisions, rather than using the exact class label. E.g. I want to vary some features ...
Marta's user avatar
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1 answer
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CNN model for binary classification

I just finished training a CNN model for binary classification. Two diagrams were created afterward, but as I am very new to machine learning, I don't get what they state. can anyone tell me if my ...
nhd's user avatar
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Which deep learning models could be used to filter right path in the binary image?

I would need some help. It is something like segmentation of a binary image. At the input is the binary image with a lot of "paths" (pixel value 1s, background 0s) and at the output, there ...
John B's user avatar
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