Questions tagged [binary]

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29 views

Reduce multiclass classification targets to binary classification targets in scikit-learn

I would like to reduce multiclass classification targets to binary classification targets. Ideally, this mapping would happen within scikit-learn so the same transformation applies during both ...
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1answer
14 views

Increase accuracy in binary classification with ambiguous data

I am fairly new to Datascience and currently working on an assignment that requires me to do a binary classification on a set with about 9 parameters for X. I tried working on it using different ...
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0answers
34 views

Keras model with LSTM quantization aware training

I would like to run quantization aware training with a keras model which has an LSTM layer. However, just the LSTM layer seems to not be supported. Alan Chiao seems to suggest here that it is possible ...
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1answer
22 views

Flipping the labels in a classification problem

Let us say A- we have a binary classifier with labels 1 as healthy and 0 as sick. The precision we got is 100% and the recall is 70%. Now let us say B-we flip the labels where 0 is healthy and 1 as ...
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0answers
12 views

How to cross validate WDBC.csv breast cancer classification dataset in Stacked Autoencoders? [closed]

I need kind guidance regarding the context of how to cross validate WDBC.csv (Wisconsin Breast cancer diagnostic) dataset for breast cancer binary classification in Stacked Autoencoders as I put the ...
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2answers
66 views

Choosing a model for input: categorised, weighted sequence, output: binary variable

What would be an appropriate model for predicting a binary target variable, given a weighted sequence? Sequences will be reasonably short, typically between ~ 1 and 5 elements. Illustrated example Say ...
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1answer
28 views

How to deal with a binary classification problem, where the instances in the negative class are very similar? [duplicate]

Let's say, one wants to detect, whether a picture of a fixed size contains a cat or not. But as a dataset, you have 10000 pictures of cats, and 30000 pictures which don't contain a cat, but are very ...
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1answer
18 views

How to set class_weight parameter for cost sensitive learning?

I'm dealing with a binary classification problem with a balanced data set, however false positives are much more costly than false negatives. Let's just say that an FP is in general 3 times more ...
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0answers
15 views

Classifier Performance - Binomial proportion confidence interval

I am solving a binary classification task. As an output of Random Forest classifier, I get a probability of how sure RF is that class is 0 or a 1. How can I calculate the needed threshold, to be 95% ...
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2answers
36 views

Is it possible the model be better on a few epochs rather than hundreds of epochs?

I have very interesting experience in my CNN binary image classification. Do you think the result is by chance or there is a logic behind it? I used InceptionV3 transfer with softmax (I know you will ...
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1answer
24 views

Preparing Dataset Minority Class vs Majority Class

I'm currently doing a binary classification for sentiment prediction. Currently I have the majority class (~90% of the data) as my positive class (labelled 1) and the minority class (~10% of the data) ...
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0answers
58 views

questions about logistic regression

In the following Linear Regression discussion I didn't understand a few things: So my questions are: In the third slide: What does this probability means $P\left(y_i|x_i\right)$ and accordingly what ...
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2answers
125 views

How to model user choice probability: binary model vs multi class model

Let's say Morpheus has multiple users to offer colored pills(from an infinite set of colored pills), there are in total 3 unique colored pills(red, blue, green) Morpheus can offer. The trick is, ...
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1answer
34 views

What is the best way to select unimportant columns for binary classification?

There is a dataset with one binary attribute (dependent variable) 0 or 1. Distribution 57/43 My task is to find such combinations of signs in which the accuracy of predictions 0/1 will increase to 70% ...
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1answer
156 views

Simple Binary Classification Example in Python

I'm not sure the correct place to ask, but I'm trying to develop a simple function/algorithm that outputs a predicted number from a sequence of numbers (I have a background in Python, but little to no ...
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1answer
33 views

Cat Classifier becomes worse the more you train it

I am using a dataset from kaggle to train a feed forward neural-neteork with no convolutional layers. I wanted to try it this was as a learning exercise with Pytorch without Transfer Learning and ...
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0answers
7 views

What is the generalization of binary/boolean matrix factorization to fuzzy logics called?

Given a matrix of boolean values $\mathbf{X} \in \mathbb{B}^{M \times N} = \{\top, \bot\}^{M \times N}$, the binary/boolean matrix factorization (BMF) problem is to find $\mathbf{U} \in \mathbb{B}^{M \...
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0answers
56 views

Forecasting binary time series

I am working on the next event occurrence prediction task and the data is binary time series with 1 if the event occured and 0 if not. I want to predict whether the event will occur or not on the day ...
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1answer
47 views

What annotators are used in Cohen Kappa for classification problems?

I am working on a classification problem using algorithms such as Logistic Regression, Support Vector Machines, Decision Trees, Random Forests and Naive Bayes. My data consists of binary class ...
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1answer
45 views

Binary classification problem with imbalanced dataset, how to compare to random classifier

We have a very imbalanced dataset (2% of class 1). To the best of our knowledge, there is no baseline in the literature to the problem we want to solve - so we thought of comparing our performance to ...
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1answer
6k views

How do I read a dat file, for which I don't know its structure?

Is there any way to atleast read the text from the dat file. I have its corresponding mdf file hence I know what all data and columns are there in it. How do I figure out the contents in my dat file. ...
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1answer
34 views

Predicting the next occurrence based on binary

I have no experience in statistics or machine learning. I have a True/False binary array describing occupation of open public spaces ...
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2answers
31 views

Does it make sense to train multiple classifiers for multiple partitions of data?

Let's say I have a dataset consisting of 100 features and a binary target variable. On exploring the data, I see that Feature 10 which is binary, seems to split the data in an 80:20 ratio with respect ...
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1answer
90 views

Using Majority Class to Predict Minority Class

Suppose I want to train a binary model in order to predict the probability of who will buy a personal loan and in the dataset only 5 percent of the examples are people who marked as bought a personal ...
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1answer
39 views

Binary Clasification Accurary

newbie speaking: Commonly we can say that accuracy is defined as total positive/ total nbr cases. But I read that, when it is a binary classifier we should consider: TP+TN/ total nbr cases. Can ...
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2answers
77 views

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show?

If in t-SNE digaram of binary classification both classes follow the similar curve what does t-SNE diagram show for instance: Figure1 or Figure2
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3answers
294 views

What is the best metric to evaluate highly imbalanaced binary classifiction? (such as fraud detection in credit card)

What is the best metric to evaluate highly imbalanaced binary classifiction? (such as fraud detection in credit card? I have examining several metrics precision recall F1 lassification Report (macro ...
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1answer
37 views

Data Science Take Home Challenge Interpretation of Question

I am currently applying for a Data Science position and have to finish a take-home challenge for one of the companies. However, I don't really understand what they want me to do and hope you can help ...
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2answers
150 views

Training model on a Balanced vs Imbalanced dataset?

Let's say that I have a 2-class classification problem where classes A & B have 10*N and ...
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2answers
21k views

How to interpret classification report of scikit-learn?

As you can see, it is about a binary classification with linearSVC. The class 1 has a higher precision than class 0 (+7%), but class 0 has a higher recall than class 1 (+11%). How would you interpret ...
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0answers
29 views

How to use “related” and “unrelated” as classes rather than multiple classes?

I have a dataset with about 15 feature columns and about 1000 rows that I'd like to use for supervised training. Every row can be classified as "related" or "unrelated" to another row. About fifteen ...
2
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1answer
109 views

Impose similar metric on segments to model

I am training a binary classifier in a dataset using AUC as a score. The dataset has two main groups (we will refer to them as good and bad population). A property that this dataset has is having a ...
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2answers
1k views

Binary classfication vs One-class classification

Why do we need samples of both classes for the training of binary classification algorithms, if one-class algorithms can do the job with only samples from one class? I know that one-class algorithms (...
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1answer
57 views

CNN for checking existance of single label

i am just thinking about training a neural network which uses data of only one single label. For example: Assuming i have many images which contain a dog. Now i want to teach the network how a dog ...
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2answers
2k views

Binary encoding and its interpretation in Python

I have a column named Street that has 2 values: Paved and Gravel. Here is what print(train[binary_columns[0]].unique().tolist())...
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4answers
217 views

Is it OK to train a binary classifier using all the extremely imbalanced data if the majority class is negative?

I'm training a neural network as a binary classifier for text classification. The data is very imbalanced, where the ratio of TRUE:FALSE is approximately 100:10000 Intuitively, it feels like using ...
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0answers
17 views

Perpendicularity between random variables?

I am reading Bechavod et al. (2017) [1], and at page 3 there is written: In the example, each data point lies in $X = (X_1,X_2) = \{0, 1\}^2$ and has two features—$X_1 = A$ is the protected ...
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151 views

Cluster method with binary variable

I need to do a cluster analysis for the following variables: ...
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2answers
96 views

Forcing class imbalance to mirror the target data

I'm trying to do binary classification on some data, my source data has a class split of 40% A / 60% B while my target data has a split of 70% A / 30% B. Is it a worthwhile strategy to use SMOTE to ...
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1answer
51 views

Anomaly Detection System

I need a sanity check. I want to create an anomaly detection system. The logic which I am planning to use is the following: Find anomalies in the past using Seasonal Hybrid Extreme Studentized ...
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2answers
179 views

Deep Learning for high contrast images with small differences

I am trying to make a deep learning classification on the gear part you can see in the images. The contrast is high and almost binary. I want to classify the images where the circle located closest to ...
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0answers
2k views

Binary Classification of Numeric Sequences with Keras and LSTMs

I'm attempting to use a sequence of numbers (of fixed length) in order to predict a binary output (either 1 or 0) using Keras and a recurrent neural network. Each training example/sequence has 10 ...
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1answer
5k views

Micro-F1 and Macro-F1 are equal in binary classification and I don't know why

I have a binary classification problem which in the test set, the number of data in both classes are equal (the test number of class 0 and class 1 are equal). Since we know that the number of samples ...
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0answers
29 views

Correct approach to usage of class labels in cell imaging data

As part of a group project at university, we are given a series of videos of cell cultures over a 24 hour period. A number of these cells (the "knockout" cells) have had a particular gene removed, ...
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1answer
75 views

Which Loss function is correct for binary mapping?

I have built a 3 layer neural network to perform a binary mapping (2016 inputs, 288 outputs.) I am getting decent results with mean square error and stochastic gradient decent. My question is: Is ...
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2answers
1k views

Using neural network for “features matching” binary classification

We have a dataset of numerical features from two images and we want to check if these images match or not using only these features. Basically we have have these columns: fA1, fA2, ..., fA14: 14 ...
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1answer
49 views

Optimal proportion between the amount of Class = 1 and the amount of Class = 0?

I am quite new machine learning methods, so I may not write proper technical formulas. My question is about the optimal proportion between sample size in Class = 1 ...
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1answer
38 views

How to include class features to linear SVM

I am planning to do a simple classification with a linear SVM. One feature I have is another classification of some sort done previously. Can I just use this class feature as a 1-hot encoded array? So,...
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1answer
288 views

Binary Classification without machine learning tools

I have to write a binary classifier for my company that should be as simple as possible and doesn't use machine learning libraries (and I also should not code too sophisticated algorithms by myself). ...
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1answer
95 views

Binary classificaiton for weather data if its class 1 or class 0 alert

I am working on weather data and it has few features that are independent variables such as severity, severity_id, ...