Questions tagged [binary]

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50
votes
9answers
24k views

How to deal with version control of large amounts of (binary) data

I am a PhD student of Geophysics and work with large amounts of image data (hundreds of GB, tens of thousands of files). I know svn and ...
34
votes
5answers
20k views

Best practices to store Python machine learning models

What are the best practices to save, store, and share machine learning models? In Python, we generally store the binary representation of the model, using pickle or joblib. Models, in my case, can be ...
19
votes
2answers
32k 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 ...
18
votes
5answers
28k views

Choose binary classification algorithm

I have a binary classification problem: Approximately 1000 samples in training set 10 attributes, including binary, numeric and categorical Which algorithm is the best choice for this type of ...
10
votes
4answers
293 views

Why might several types of models give almost identical results?

I've been analyzing a data set of ~400k records and 9 variables The dependent variable is binary. I've fitted a logistic regression, a regression tree, a random forest, and a gradient boosted tree. ...
9
votes
1answer
312 views

Using SVM as a binary classifier, is the label for a data point chosen by consensus?

I'm learning Support Vector Machines, and I'm unable to understand how a class label is chosen for a data point in a binary classifier. Is it chosen by consensus with respect to the classification in ...
9
votes
3answers
582 views

Binary (Unary) Recommendation System with Biased Views

I would like to create a content recommendation system based on binary click data that also takes views into account. What content a user has been exposed to, and therefore has the chance to click ...
7
votes
2answers
1k views

Why are precision and recall used in the F1 score, rather than precision and NPV?

In binary classification problems it seems the F1 score is often used as a performance measure. As far as I've understood the idea is to find the best tradeoff between precision and recall. The ...
6
votes
3answers
455 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 ...
5
votes
1answer
7k 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 ...
5
votes
3answers
256 views

How to create an ensemble that gives precedence to a specific classifier

Suppose that in a binary classification task, I have separate classifiers A, B, and C. If I ...
5
votes
1answer
191 views

how can I generate a Bernoulli block mixture model in matlab?

I am trying to write the code of a Bernoulli block mixture model in matlab, but am facing an error every time I run the function. In particular, I'm having a problem with how to relate the ...
4
votes
2answers
20k views

Is a correlation matrix meaningful for a binary classification task?

When examining my dataset with a binary target (y) variable I wonder if a correlation matrix is useful to determine predictive power of each variable. My predictors (X) contain some numeric and some ...
4
votes
1answer
3k views

Sklearn Aggregating Multiple Fitted Models Into A Single Model? (binary classification)

My problem context: dataset too big to fit into memory. binary classification [0,1] 30 csv files in a directory with exactly 30,000 samples (rows) each file contains 15,000 ...
3
votes
1answer
2k views

Binary classification toy problem

I'm trying to build a toy model which can identify a constant difference between two variables: (if variable1- variable2>10 then 1 else 0). This should be a ...
3
votes
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 ...
3
votes
1answer
57 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 ...
3
votes
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 (...
2
votes
2answers
515 views

Cluster very many sparse binary vectors

I have a very big set of high-dimensional, but sparse binary vectors. Each vector represents a "one-hot-style" n-gram sequence of words where each index of the words that occur in the n-gram is set to ...
2
votes
2answers
131 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, ...
2
votes
1answer
18 views

Can you choose a binary feature matrix for a binary classification model

This may be a stupid, but, I am new to deep learning (and machine learning for that matter) and I can't seem to find any literature to help with my question. All I can see when Googling many different ...
2
votes
1answer
119 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 ...
2
votes
1answer
38 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 ...
2
votes
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,...
2
votes
1answer
66 views

Predicting or patron find of a binary variable over time

I'm new to ML and trying to find some practical use to it I encountered with the chance of saving the connections and disconnections (the binary variable) of a bunch of users like this: "User A ...
2
votes
0answers
11 views

Best Approach and Classifier for Binary Classification Problem

I am trying to build a binary classifier, and I am wondering what is the best approach for data segmentation, training/testing, performance evaluation, selecting classifier type, and overall approach ...
2
votes
0answers
123 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 ...
2
votes
1answer
32 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 ...
2
votes
1answer
112 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 ...
2
votes
0answers
30 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, ...
2
votes
0answers
1k views

Backpropagation with step or threshold activation function

I understand that gradient descent is local and it deals only with the inputs to the neuron, what it outputs and what it should output. In all I've seen, gradient descent needs the activation function ...
1
vote
4answers
258 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 ...
1
vote
1answer
323 views

decision rules for each feature (binary classification)

I have a collection of 10 features (all numerical) and a single binary outcome variable. I need to train a binary classification model, find the best features and compute thresholds for each feature. ...
1
vote
1answer
1k views

Binary Neural Network Classification or Multiclass Neural Network Classification?

I am confused about the difference between a binary and multiclass neural network classification. If I am writing an algorithm that has 2 output classes (Obama or Romney), but not yes or no (so not ...
1
vote
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())...
1
vote
1answer
146 views

Significant overfitting with CV

I working on a binary classification task. The dataset is quite small ~1800 rows and ~60 columns. There are no duplicates in the rows. I am comparing different classifiers amongst the canonical ones: ...
1
vote
1answer
93 views

Understanding outputs from ANN and how to improve validation loss

I apologise if this is a bit long winded, but it was suggested by another user that I post. I will start by saying that I am very new to the world of machine learning and deep learning. As such, the ...
1
vote
2answers
69 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 ...
1
vote
1answer
25 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) ...
1
vote
1answer
233 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 ...
1
vote
2answers
184 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 ...
1
vote
1answer
81 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 ...
1
vote
1answer
360 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). ...
1
vote
1answer
52 views

What Kernel is suitable for the following data for SVM classification?

I have the following 2 class data, as shown below. . Its a hand crafted example using two ellipse equations. I want to know what might be a recommended kernel to be used with this problem if I want ...
1
vote
3answers
180 views

adding logic combinations of boolean features in classification

I want to build a classifier from a dataset of vectors that include exclusively boolean values. Is there any chances that my classifier might perform better if, previously to the learning, I add ...
1
vote
1answer
24 views

Making an ensemble model for high F1 score

I presently have 2 algorithms that have a numerical output. Using a threshold of 0.9, I get the classification output. Let's say they are: P (high precision, low recall) R (high recall, low precision)...
1
vote
0answers
51 views

Pearson correlation on two categorical variables

I am using the fourth-corner method in one of my papers (for those who need the name). The method was developed to test associations between variables in two datasets. In my case, the datasets ...
1
vote
1answer
35 views

Binary Cross Entropy | Manual scalars [closed]

I am wanting to make print statements "showing my working out" of Binary Cross Entropy loss function, that works with ...
1
vote
0answers
32 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 ...
1
vote
1answer
30 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 ...