Questions tagged [binary-classification]

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1 answer
244 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 ...
0 votes
1 answer
70 views

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. ...
0 votes
1 answer
73 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), ...
0 votes
2 answers
123 views

How to deal with temporal trend in ML

I am fitting a binary classifier and I observe a temporal trend in the response variable, meaning that the actual percentage of positives fluctuates with time, I can see periods where it is high and ...
0 votes
0 answers
19 views

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?&...
1 vote
1 answer
53 views

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 <...
0 votes
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 ...
4 votes
1 answer
290 views

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 ...
0 votes
1 answer
75 views

Aggregation of low level features for a classifier

The objective is to predict router fail/no fail (1/0) in a future time window with all the data collected over the last hour (i.e. binary target) The data is received at two different levels: Router ...
0 votes
0 answers
19 views

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? ...
3 votes
2 answers
213 views

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 ...
0 votes
0 answers
55 views

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. ...
1 vote
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 ...
2 votes
2 answers
1k views

Is it vital to do label encoding with target variable

Should I always use label encoding while doing binary classification?
0 votes
1 answer
387 views

Which classification_report metrics are appropriate to report/interpret for a binary label? Individual or macro average for both classes? scikit-learn

First, please forgive my ignorance; I am a newbie but dedicated to learning more. Example: I have a using a random forest classifier to predict a binary outcome. The binary outcome equals 1 if people ...
1 vote
1 answer
895 views

Loss drops to NaN after a short time for a time series classification

here is my model code for a binary classification of a time series: ...
0 votes
1 answer
155 views

Text Classification misclassifying?

I am trying to solve a binary classification problem. My labels are abusive (1) and non-abusive (0). My dataset was imbalanced (more 1 than 0s) and I used oversampling of the minority label (i.e. 1) ...
1 vote
1 answer
782 views

Finding logistic loss/negative log likelihood - binary logistic regression classification

I am new to ML and data science and am struggling with a simple problem. In my problem, I am given a series of datapoints $X_i$ where $X_i = (x_{i1}, x_{i2})$ with each data point having a label $y_i$ ...
0 votes
0 answers
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 ...
1 vote
1 answer
43 views

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 ...
0 votes
0 answers
14 views

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 ...
0 votes
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: ...
0 votes
0 answers
45 views

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, ...
0 votes
1 answer
255 views

What is the best practice to normalize/standardize imbalanced data for outlier detection or binary classification task?

I'm researching Anomaly/outlier/fraud detection, and I'm looking for the best practice to pre-process the synthetic data for imbalanced data. I have checked all methodology for normalizing/...
0 votes
0 answers
26 views

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 ...
0 votes
1 answer
204 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 ...
0 votes
0 answers
24 views

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 ...
0 votes
3 answers
84 views

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 ...
0 votes
0 answers
24 views

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 ...
0 votes
0 answers
15 views

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 ...
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 ...
0 votes
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 ...
0 votes
2 answers
54 views

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 ...
0 votes
0 answers
81 views

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 ...
0 votes
0 answers
70 views

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 ...
0 votes
1 answer
420 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 ...
0 votes
1 answer
12 views

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 ...
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 ...
0 votes
3 answers
202 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 ...
0 votes
2 answers
219 views

How to visualize data after performing OneHotEncoding and normalization?

I have a dataset and on that, I have performed OneHotEncoding and Standardization using standard scalar, Now that I have preprocessed data I have to visualize it, but on converting it to pandas ...
0 votes
1 answer
148 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 ...
0 votes
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 ...
0 votes
1 answer
217 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 (...
1 vote
0 answers
19 views

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 ...
0 votes
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 ...
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. ...
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 ...
0 votes
0 answers
147 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 ...
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 ...
0 votes
1 answer
321 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 ...