Questions tagged [binary-classification]
The binary-classification tag has no usage guidance.
129
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Top 2% of scores of a binary classifier are 100% class 1
I have a binary classification model (Xgboost) that is supposed to be predicting whether a customer will be purchasing a service.
Overall the metrics are satisfactory ~.67 AUC, ~30% precision and ~40%...
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How to prepere dataset for binary classification (anomaly detection?) on timestamped sensor data (multiple files)?
my goal is to make prediction (good or bad data) on sensor data. I tried a lot, but failed to shape my data to get the desired output.
scenario:
I have multiple timestamped (time as it self is not ...
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Creating a custom layer in tensorflow
I'm trying to create a layer in TensorFlow, which works something like this:
And my implementation looks something, like this:
...
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How to combine binary classification with patient stratification?
I am working on a binary classification model (healthy/diseased) based on gene expression data of different patients. As a second task, I would like to stratify these patients and find subgroups.
I ...
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TSNE interpreration and separability
I have a binary classification problem where I train a neural network on a training and validation data sets. But I am not satisfied with the performance of my trained classifier (the NN above). The <...
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Python xgboost predicting future events
This is related to this article: https://towardsdatascience.com/forecasting-of-periodic-events-with-ml-5081db493c46
I found it interesting and tried to replicate it, having as a result a xgboost ...
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606
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If I have two variables with strong correlation, should I delete one and leave the other in my data
I have a large dataset, where I should make a binary prediction. The fact is that, after analyzing the data, I found that some variables are positively correlated to each other. So, I was wondering ...
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How to deal with Different Shapes of X_train and X_test after OneHotEncoding?
I am trying to perform OneHotEncoding as well as feature scaling on my training and testing data separately, steps I did:
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2
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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 ...
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3
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902
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How are scores calculated for each class of binary classification
The formula for Precision is TP / TP + FP, but how to apply it individually for each class of a binary classification problem,
For example here the precision, recall and f1 scores are calculated for ...
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Binary document classification using keywords for a very small dataset
I have a set of 150 documents with their assigned binary class. I also have 1000 unlabeled documents. Each document is about the length of a journal paper. Each class has 15 associated keywords.
I ...
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Excluding data via confidence score: Is it a good idea?
Let's say I have a model which has a binary classification task (Two classes of 0 and 1) and therefore, it outputs a number between 0 and 1, if it is greater than 0.5 we consider it to be class 1 and ...
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378
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How do you add negative class sample for binary classification?
How do you prepare the negative dataset for binary classification? Let us say that I am building a classifier that has to classify whether the input image is of a car or not. I already have a dataset ...
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Non-Classification outputs in a classification problem
maybe this is a very stupid question, so please excuse me as I am a total beginner in Machine learning.
I have a dataset divided into X (shape: 10000, 599), Y(shape: 10000,). Y is simply zero or one. ...
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Should I balance the test set for predicting probabilities in binary classification?
In my dataset I have 75 % of "0" class instances and 25 % of "1" class. It a real world ratio between classess. I balanced my training set, and trained the model.
Then, depending ...
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70
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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 ...
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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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logistic regression or density estimation for binary dependent variable and binary (or categorical) features [closed]
I have a binary dependent variable $t$ and categorical features. We can even simplify to binary features since I can one-hot encode the categorical variables. In practice the one-hot encoding induces ...
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137
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Binary Classification with Imbalanced Target [closed]
I have a dataset and my objective is to run a Binary Classification, but my target feature, that is supposed to have "True" and "False", only has "True", as a value.
I ...
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Why does my InceptionV3 model give a high training accuracy (99%), a high validation accuracy (95%+) but a very low testing accuracy (55%)?
Note: Please go through this in its entirety.
My objective here is not just to get a high testing accuracy but to explain why it is so low in spite of validation accuracy being so high.
I am a ...
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365
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using Reinforcement learning for binary classification
I want to build an agent for binary classification. I have a large dataset with two label (0 and 1). I want to build an agent to predict labels. I build a deep model and now I want to build an agent. ...
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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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How to choose the right threshold for binary classification?
I am currently working on the titanic dataset from Kaggle. The data set is imbalanced with almost 61.5 % negative and 38.5 positive class.
I divided my training dataset into 85% train and 15% ...
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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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How can compare suggestion models with different performances?
I have 4 class binary classification models. That models identify which class a particular students is suitable for.
For example, we have user 1 and 4 classes ...
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ZeroR as performance baseline for binary classfication model?
It is known that ZeroR model is used predict the majority class in a given data set.
Having said that, is ZeroR a suitable performance baseline provided one has a balanced data set (50/50)?
If not, ...
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1
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243
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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/...
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151
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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) ...
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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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