Questions tagged [binary-classification]
The binary-classification tag has no usage guidance.
61
questions with no upvoted or accepted answers
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Obtaining threshold based rules for classification problem
Suppose there are X1...Xn numerical variables predicting a target variable Y (0 or 1)
Objective: to obtain the best possible thresholds and combinations of X1...Xn that can predict Y
Example: (X1>...
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Is it vital to do label encoding with target variable
Should I always use label encoding while doing binary classification?
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123
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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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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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Data filtering framework
I have procurement data that needs to be labeled with product categories. It's tabular data, containing 700k rows and a mix of data types (dates, free text, floats, etc.) The product set we currently ...
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22
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Best way to represent a version feature based on percentiles
We're training a binary classifier in AutoML, and one of the features consist of browser versions.
Currently these versions are provided "normalized" to the model, according to the ...
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24
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Repeating values caught with a binary classifier
If my machine is broken, it starts to repeat certain channels. Thing is if there are no out-liars, it is difficult to tell it's broken as we would expect all data points to be around the same value. I ...
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1
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How to customize logistic regression for this case?
I have a binary classification problem, with a dataset comprising of several features. When I train LogisticRegression on it, I get large number of false positives ...
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36
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Fractional Differencing/Differentiation for Non-Time based Model; Look-ahead bias?
I have time-series data, but instead of using a time-based model like RNN, I've decided to approach my classification problem using an lgbm classifier. To do so, I have modified the data, such that ...
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Suggestions for binary time-series-classification model for small dataset
Hopefully I´m at the right place for my question:
I´m looking for suggestions for models to use to classify multivariate time series. I´m trying to find a way of classifying the behaviour of motors ...
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1
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639
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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 $y_i$ ...
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848
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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:
...
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315
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How to pass manually split data to cross-validation
I have to perform a binary classification. My dataset is quite small 280 samples and quite imbalanced (1:10 ratio). I kept around 100 sample as testing and about 140 for training. My input variables ...
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31
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Testing a Binary Classifier
I have been training a binary multilayer perceptron on a database made out of roughly 3600 0 values, and 4 1 values. Afterwards, I'm testing the MLP on a test set made out of 7 0 values and 7 1 ...
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52
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Classification problem with 2 level features
Consider an automated house, where we can collect router data every minute. The objective is to predict router fail/no fail (1/0) in a future time window.
The router sends data at two different levels ...
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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 ...
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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 ...
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2
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27
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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:
...
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41
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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, ...
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21
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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 ...
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22
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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 ...
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1
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33
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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.
...
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23
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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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12
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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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59
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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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49
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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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1
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12
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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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0
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11
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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 ...
0
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1
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48
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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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180
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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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1
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95
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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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50
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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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17
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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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7
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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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8
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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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107
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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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13
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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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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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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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245
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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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52
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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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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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How to cluster data where each sample has a different amount of different features?
I decompiled one million binaries and stored a representation of every function in a database.
Each binary has a list of functions.
Each function has a number of callees (how often its called by ...
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327
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Classification report for binary class problem
I am building a binary CNN using single neuron in the last dense layer and "binary_crossentropy" as the loss function while compiling to predict either class1 or class2. I am having problem ...
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1
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Understanding Classification model results
In a certain binary classifcation problem I am getting a AUC of 1 and Accuracy,FI,Recall,Precision of ~99.7 both in train,test and holdout sets.
But when I run the model on unlabelled data which I ...
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Sampling Highly Imbalanced Large Dataset
I am working on a model which will run monthly on 8M users. I've snapshot-wise data in training set, eg:
Jan, 21 Snapshot : 8M Total : 233 Positives Rest Negative
Feb, 21 Snapshot : 8M Total : 599 ...
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1
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45
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Give more weight to features based on distribution plot
I have a task to predict a binary variable purchase, their dataset is strongly imbalanced (10:100) and the models I have tried so far (mostly ensemble) fail. In ...
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1
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330
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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 ...
