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Questions tagged [feature-engineering]

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1answer
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Why feature crosses may work better than having them as individual features?

On Google ML Crash Course it is said the following: If we build a feature cross from both these features: [behavior type X time of day] then we'll end up with vastly more predictive ...
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14 views

Feature selection through Random Forest and Principal Component Analysis

I am working on a binary classification problem and I have 870 numeric independent features to start with. I tried PCA on input features and picked top 200 variables corresponding to first 10 ...
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3answers
57 views

How to understand features impact in a non linear case?

I give a simple example: I have a set of houses with different features (# rooms, perimeter, # neighbours, etc...), almost 15, and a price value for each house. The features are also quite correlated (...
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12 views

Should I use feature reduction or feature expansion with the hashing trick?

I am working on a task to predict the delay time of a flight. For this, I am allowed to use a subset of the features from the carrier-on performance dataset. The ...
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1answer
32 views

How to use one hot encoding of string categorical features in keras?

I am dealing with a binary classification problem. The output column of my dataset is already encoded in 0/1. The problem is that I have many categorical features (columns), which are strings and I ...
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2answers
24 views

model to predict annual outcome based on previous years data

I have below datasets for two years each holding about 10.000 records. Every week a new report is generated that shows the performance for the current or any previous month. Therefore a more recent ...
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0answers
13 views

How to discretize numerice values with predfined ranges in weka?

I'v imported csv file into weka. one of the features have a value with minimum 0 and maximum 160. now, i want to discretize value into three range as you can see below: less than 6 > L more than 6 ...
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2answers
60 views

Feature engineering from date, mean and standard deviation

I have a multi class classification problem where I should predict the passengers for flights (0-7 classes). The training set consists of the following features: Date of the flight Mean of the weeks ...
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13 views

Data leakage and predictive models: should we use past predictions as a feature?

I want to develop a Random Forest Classifier model to predict whether or not a customer will convert 7 days from today. The model is re-trained once a week and makes predictions for the following week....
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3answers
67 views

how to evaluate feature quality for decision tree model

Most of the tutorials assume that the features are known before generating the model and give no way to select 'good' feature and to discard 'bad' ones. The naive method is to test the model with new ...
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1answer
30 views

Who wrote the formula for gini importance/sklearn's feature importance score?

I've been looking for a paper where the Gini importance was first proposed, but I am not sure if this is actually how it came to be. Here's the formula I am familiar with and am looking to find in a ...
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0answers
10 views

Target Encoding for test dataset

While training, i have used target encoding, to built some features, but i am wondering, how to encode features for test data-set? One way, i can recall, is to use training dataset, to encode ...
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1answer
22 views

Creating a Feature to determine popularity

I am Building a Recommendation System in which i have Multiple Category , I want to Know how Popular is my Product in each Categories. For that I am considering Probabilty as one factor. For e.g I ...
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0answers
11 views

What is cross-labeling?

In an online course I just heard that cross-labeling the Input data improves the accuracy of a Neural Network classifier. Can someone explain what it is and how it influences the accuracy ? Google was ...
1
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1answer
84 views

Generating Polynomial Features in R

Is there an optimized way to perform this function "PolynomialFeatures" in R? I'm interested in creating a matrix of polynomial features i.e. interactions between two columns among all columns but I ...
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1answer
22 views

Queries regarding feature importance for categorical features

Queries regarding feature importance for categorical features: Context: I have almost 185 categorical features and these categorical features have either 2 or 3 or 8 or 1 or sometimes 4 categories, ...
2
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1answer
27 views

Should I create metafeatures for my XGBoost training set?

Say I've got two (not necessarily independent) features A and B for my dataset. Should I create metafeatures from them? say for ...
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2answers
24 views

How important is it for each row of data to have the same number of features?

I'm using decision tree learning to try and classify a device based its components. Different devices have a different number of components and the location of these components within the device is ...
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0answers
21 views

Should I concatenate one-hot vectors and real vectors as input feature?

I have a set of input features consisting of the following for each row of data: real vectors (1x128 dimensions, between [1,1000000000] ) one-hot vectors ( 1x168 dimensions, i.e. 7 days 24 hours ) ...
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2answers
48 views

How can I improve a machine learning model?

I am a Machine learning newbie and i am trying my hands with a dataset which has 9 features and my aim is to figure out the optimal multi class classification model which fits my dataset. I applied ...
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2answers
36 views

data pre-processing before image classification

I'm working on a machine learning project, Images classification (shape: 100 x 100)-> (vector of 10000), I did some pre-processing before applying decision trees algorithm , I got an accuracy of 55 % ...
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0answers
41 views

Layman's explanation of when to use which smoother algorithm/technique: FFT, loess, Savitzky-Golay, etc

As an analytics practitioner, I frequently come across noisy data (e.g. IoT data). When building a model or machine learning algorithm, it can be advantageous to smooth this data. Over the years, I ...
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0answers
18 views

One-Hot Encoder and nested categorical features

Suppose we have a dataset with $n$ features $A_1,\cdots,A_n$ that are categorical and are nested. By nested, I mean if you know the categorical value of $A_m$ for observation $x$, then the value for $...
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1answer
16 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
50 views

Why would a fake feature with random numbers get selected in feature importance?

I'm using a sklearn.ensemble.RandomForestClassifier(n_estimators=100) to work on this challenge: https://kaggle.com/c/two-sigma-financial-news I've plotted my ...
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1answer
44 views

Is a neural network able to learn to map a completely different feature vector to the same class

Is a neural network (for example a MLPClassifier in Python) able to learn to map a completely (or very) different input feature set to the same output class? Or is it better to work in this case with ...
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1answer
20 views

Effect of adding extra unrelated features to linear perceptron

Suppose that we are training a linear regressor (perceptron). Adding extra features that are not related to the target (e.g. randomly generated values) before training will typically ____ our training ...
2
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1answer
24 views

“help” decision tree by tying 2 features together

Assuming I have in my dataset 2 (or more) features that are for sure linked (for example: feature B indicates the amount of relevance of feature A), is there a way I could design a decision tree that ...
0
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1answer
23 views

Is it correct to use non-target values of test set to engineer new features for train set?

Suppose, I have a dataset with a feature_1 value and a target value. Now, I want to engineer a new feature by creating relative value by subtracting mean from each value. Question: Can I (1) use ...
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0answers
15 views

How to construct an wealth feature for an area, rate or density?

I am trying to model a house price predicting. I have some socioeconomic data according to the postcode area, such as: high income inhabitants, middle income inhabitants, low income inhabitants, ...
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1answer
28 views

How to handle “not label Y” in a multi class machine learning problem?

I have a train data set that comprises information in the form: ...
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0answers
12 views

How to optimize the separation of two distributions from binary classfication

Given a sample where for each individual a classification is predetermined (e.g. sick or not) and 5 random variables are measured. The random variables are on the same scale but from differnt bins. E....
2
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1answer
28 views

I want to create an additional feature(column) based on some manipulation of values from existing features

Consider my data-frame to be like this ('x','y','z' are features): I want to create a python function which will take an expression as a string (something like this: 'x+y-2z') and create a new ...
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0answers
43 views

Handling missing values to optimize polynomial features

I was playing around with some data to practice my Python and machine learning skills and wanted to create polynomial features from two features that I think are related and have a strong influence on ...
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0answers
25 views

Handle outliers, Losing many data by removing natural outliers

I have 2 skewed features, here is the summary of one of the features ...
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1answer
26 views

Predicting a cyclic target

I'm familiar with using trigonometric functions to transform cyclic variables for use as features in training a model (most commonly hour of the day or month of the year); I'm now trying to figure out ...
1
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2answers
48 views

Feature engineering decrease my cross validation

I'm currently working on a fraud detection data set. I'm evaluating my training data with a 10-skfold roc auc and an estimator of default param LightGBM. But, the problem is every time I try to create ...
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3answers
28 views

Equivalent of numeric encoding when rows can contain multiple values

If we have a column such as Name 0 Alice 1 Bob 2 Dave then, after numeric encoding, it becomes ...
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0answers
48 views

Beginner Question Related To Data Science Course [closed]

I am Third Year B.Tech student from 3-tier college of India ,Here is no one fellow or collegous who has somebit knowledge about ML or Data science and I am purely sure that I have strong background of ...
3
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1answer
101 views

Creating similarity metric with Doc2Vec and additional features

I have a dataset which contains many features. Each record is company that has many features. For example... Company A: Keywords - data, big data, tableau, dashboards, etc. Industry - Information ...
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0answers
15 views

Suggestions on using model in production 1 test at a time

I have created an Artificial Neural Network with 4 categorical features and a binary outcome either 1 for suspicious or 0 for non-suspicious: ...
3
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3answers
92 views

How to handle large number of features in machine learning?

I try to do normal classification on high dimensional traditional columnar data (several hundred columns). The features are of different type. In this case, it's clearly out of question to examine ...
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2answers
66 views

How to integrate time series data into normal features for machine learning?

I confront a problem where one data source is a "normal" DF with customers as rows (each customer occurs once) and static customer features as columns. The other DF other hand is a big pile of ...
1
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1answer
60 views

Imputation missing values other than using Mean, Median in python

I heard that Mean, Median isn't the best way to impute the missing values, why would that be? In my scenario, I have data like this ...
2
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0answers
36 views

Metrics to evaluate features' importance in classification problem (with random forest)

I want to evaluate the importance of each of the features of a 2000x60 dataset in a classification problem with random forest. The most widely used ones apparrently are: Cross Entropy-Information ...
3
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2answers
40 views

Dummy variable for Categorical values

The question is in reference to solution of Titanic survival predictionat kaggle . As many have did the similar kind of feature extraction, They have converted some of the numerical features (Age, ...
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0answers
10 views

Assigning scalar values for PID for order in Neural Network

I have built a neural network using Windows Process's I started off with only two features, the file path with parent process, and the file path with child process. I am slowly adding features for ...
1
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1answer
22 views

Using historical label as a feature in my ML model?

I am working on a predictive model to predict change in the price of an asset (up, down, no change). The labeling is based on the derivative of the price and is exponentially smoothed with an alpha of ...
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0answers
28 views

Adding and Normalizing extra features to Word2Vec representation

My problem is kind of similar to this question I am currently using a word2vec 100 features representation of my words. However, I want to add more features to have more similarity between synonyms ...
0
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1answer
50 views

kde plot for interpreting the correlation

i have created some new features for my model. I found people use kde plot to find out the correlation between the created feature and the target variable, but I am not really sure how to find the ...