Questions tagged [binary-classification]
The binary-classification tag has no usage guidance.
126
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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58
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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 ...
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3
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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 ...
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1
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45
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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 ...
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1
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44
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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), ...
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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 ...
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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 ...
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28
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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.
...
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59
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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 ...
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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 ...
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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 ...
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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 ...
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59
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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
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66
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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 ...
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171
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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 ...
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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 ...
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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 (...
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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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46
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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 > ...
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40
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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 ...
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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 ...
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229
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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 <...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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1
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117
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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 ...
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3
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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 ...
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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 ...
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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 ...
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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 ...
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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, ...
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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 ...
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79
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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 ...
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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 ...
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