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Questions tagged [correlation]

A measure of the degree of linear association among a pair of variables.

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Measuring Effects of Multiple Changes over Time

I'm writing a social media marketing plan for a website. I have several changes I am planning to implement (increasing posting rate, changing type of content posted, etc.) over an extended timeline to ...
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How to statistically prove that a column in a dataframe is not needed

I have a pandas dataframe consisting of dimensions and features of a different fabric materials. I have several rows per product material type causing the dataset to seem very huge. From basic logic ...
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Regression or Correlation for this RQ?

Our little group at uni is investigating if there is a relationship between 3 measures of social well-being (social anxiety, social connectedness and self esteem) and usage time (on-screen time in ...
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Visualizing correlation with large number of features

Often, visualization is touted as a prerequisite to model building, with the purpose of identifying features which are correlated with each other (think NxN correlation grid graph). The correlated ...
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Spearmanr on two pandas dataframes

I have two pandas dataframes that look about the same but with different information stored in them. My question will be about how to compare the two dataframes to ensure column and row match before ...
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How to find correlation among multiple attributes in group by dataframe object?

I have a data frame with following attributes : CP - Counting point of vehicles A-Junction - Starting node of a road ...
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Feature selection for time series prediction

I'm working on an LSTM-based stock market forecasting problem and trying to figure out a way to select input variables. When calculating correlation between variables (e.g. Close price of Tesla vs ...
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Problems with Graphical Lasso

I'm trying to use the Graphical Lasso algorithm (more specifically the R package glasso) to find an estimated graph representing the connections between a set of nodes by estimating a precision matrix....
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Robust method to extract “pure” part of a variable

I am trying to perform a multi linear regression model: $$y_i = β_0 + β_1x_{i1} + β_2x_{i2} +... + β_px_{ip} + ε_i$$ where $$x_{i1}, x_{i2}, ..., x_{ip}$$ are highly correlated with each other (VIFs ...
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Is there any logic to adding a threshold to see if two variables are related?

I have two variables $X$ and $Y$ given as tuples of $(x, y)$, and I want to see if there is a relationship between the two variables. I can do so by finding the correlation coefficient. However, I ...
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Looking for correlation between a big set of variables: divided in groups or all together?

I have a tiny classified dataset (2 classes and over 20 samples for each class) where I would like to find the highest pair-correlated variables. I doubt if I should mix both groups of samples and run ...
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automatic feature selection

I have a lot (thousands are possible) of automatically-generated ordinal features that i'd like to exploit , to differentiate between two classes. I'm looking for some measure that will select the ...
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Representing cyclical features as sin/cos components

I'm working on a prediction project where we have a lot cyclical features such as hour of the day, weekday, month, day of year, etc etc. After some searching I decided to follow the advice here. Now ...
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Time Posting Data Analysis

I work in a professional services company and would like to get some analytics on how discipline the fee earners post their times to the system may have an impact to the revenue. One area that I am ...
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What is the relationship between correlation ratio and one-way Anova?

According to the answer to this post, it is recommended to use one-way anova to compute the dependence between a categorical and a numerical variable. Besides, the second answer to this post says ...
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Finding the correlation between categorical variables

I'm working with a dataset of roughly 40000 files, each of which is the full text of a novel. I've found the percentages of words in each novel that belong to different mutually exclusive categories ...
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Correlation analysis and augmented dickey fuller test

I am performing the correlation analysis for each of the sectors (consumer discretionary, consumer staples, financials, technology, etc.) and the MSCI ACWI index. I am using their daily return data to ...
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Regression algorithm for weak correlated target and features

I have a regression problem in hand. Dataset have 20 predictors and 1 target. Target is continuous and predictors are both categorical and continous. I performed a correlation test between continous ...
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How to Classify X Column to the correlated Y Column?

I'm having trouble to attack this "classification" problem, with some pattern recognition. I need to classify a whole X column to the correlated Y column. For example, Classify the data in column X2 ...
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Random Forests with complementary features

In my dataset, I have 2 features that are not only correlated but that makes sense only in the presence of each other. For instance, one would be the number of times a task was attempted and the other ...
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Standard correlation coefficient of various datasets

I understood the correlation coefficient of the first line. But the correlation coefficient of second and third line differ with the first line in figure 1. Why is it so ?. Even the shapes differ for ...
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Chi-squared for continuous variables

I am using chi-squared to determine feature importance as I select features to train a supervised ML model. I create a contingency table for the feature/target, and feed this contingency table into ...
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Is Pearson coefficient a good indicator of dependency between variables?

Once I have been asked how would I calculate correlation between two time series. Since I am new to data science I answered: "I would just calculate the Pearson correlation coefficient". That wasn't a ...
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How do i interpret this correlation

Does this mean that as long as the student has good gpa and good gre even though his Alma Mater's prestige is low - he will get admitted in a college Any additional things i can interpret from below ?...
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Discarding correlation among inputs in a neural network

I am working on a problem with 4 inputs and 1 continuous output variable. The sum of all values of the 4 input variables is always 1. a1+a2+a3+a4=1 So, they are correlated. My question is: ...
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Adjusted coefficient pearson as CNN loss function

I am trying to create a CNN (using python Keras) that runs on medical images of cancer and classifies them as cancerous or not. (Sample sizes vary between 30,000-280,000 on each trial run). As an ...
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How do different models take in account independence/dependence of features?

How do different models take in account independence/dependence of features? I've only found very rough "pointers" as to what assumptions different models make about the independence/dependence of ...
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Is it the job of the modelling approach to consider or not consider independence/dependence of features? Or should it be known before-hand?

I'm confused, Is it the job of the modelling approach to consider or not consider independence/dependence of features? Or should it be known before-hand? If I know nothing about independence/...
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135 views

Why is a correlation matrix symmetric?

I'm sorry for being so weak in math. (I'm a student) For eg. this is a correlation matrix. ...
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43 views

What are some data sources with strong positive and negative correlations in feature and sample space?

For example, financial data has in some cases strong positive and negative correlations between different stocks (feature space) and also strong positive and negative correlations between specific ...
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Making sense of kernel canonical correlation analysis weights in the original space?

Kernel Canonical Correlation Analysis offers a non-linear alternative solution to the classical Canonical Correlation Analysis by first projecting the data into a higher-dimensional feature space. A ...
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63 views

Correlated features and double dipping

I am performing a machine learning analysis of MRI data. I have an extremely large number of features, thus I decided to remove highly correlated features and I decided to perform this step ...
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Algorithms affected by multicollinearity due to correlation between independent features

Please help me in understanding which and all machine learning get affected by Multi-collinearity due to the correlation between the independent features.
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How do I determine if variables are correlated? Is it simply a mathematical calculation?

I'm self learning data science so bear with me as I try and make my question as clear as possible. Lets assume I have a dataset of a dependent variable y and some independent variables x1, x2 and x3 ...
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Generalization of Correlation Coefficient

The correlation coefficient tells me how two variables (sequences of numbers) are correlated with each other. Does it generalize to non-linear scenarios? How could one more generally measure the ...
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Clustering a contingency table

I have a contingency table listing individuals with certain traits. For the sake of simplicity, let's say the table has individuals in rows, and the type of food they like in columns: ...
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Correlation between products

I have a huge set of past sales data and I would like to know if there are correlations between the products (for example if a client buys product A he is 80% more likely to buy product B... If a ...
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Fill missing continuous values using Machine Learning models

Is it a good idea to fill missing data with ML models, like Linear Regression or KNN, that use other highly correlated features to make predictions?
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Is it advisable or okay to view heatmap of categorical features?

As the title suggested. By default sns.heatmap will not include categorical features which are not factorized. Since factorized categorical features do not behave like a scale (eg. Quality: 0-10), I ...
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Weight visualization for the Deep Canonical Correlation Analysis

In the case of the linear Canonical Correlation Analysis (CCA), one can easily visualize the weight vectors. This helps with intuition about which parts of the input are mainly responsible for the ...
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Finding correlation between categorical feature and the continuous features

First, I have some missing values in the dataset. To find out the correlation among variables I need to fill the data first which I did. Next I have to find correlation between categorical feature and ...
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Autocorrelation of a sine wave

I would like to know the meaning of an autocorrelation graph of a sine wave. When the time lag is 0, then the autocorrelation should give the highest value of 1 since a copy of the signal is ...
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Quantiles for queuing processes with exponential arrivals and Pareto departures

I am generating the data from process $X_{n}= X_{n-1} + U_n - W_n $ where $ U_n= [U_{n1}, U_{n2}]$ is bivariate exponential process with correlation and $W_n= [W_{n1}, W_{n2}]$ is bivariate Pareto ...
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How should I unify this type of variable?

I have the following problem: I have a variable that is composed by N levels and I want to find out if other numeric and continuous variable is correlated with this ...
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1answer
316 views

Is it good practice to always remove highly correlated variables?

1- Would it always be beneficial to remove highly correlated features prior to training a model? If not, why not. 2- Would you perform One Hot encoding where applicable, prior to removing highly ...
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How does multicollinearity affect neural networks?

Multicollinearity is a problem for linear regression because the results become unstable / depend too much on single elements (source). (Also, the inverse of $X^TX$ doesn't exist so the standard OLS ...
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472 views

Calculating correlation between two time variables

I have a dataset that looks like this : ...
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Calculating correlation of slightly out of sync data

I am trying to do some analysis on some data that comes from special glasses that track a few things including pupil size and gaze velocity. I would like to calculate the correlation between two ...
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147 views

which neural network topology to learn correlations between time series?

I have two (or more in principle) 1xN time series, and I would like to train a NN to predict the next value of both. I can arrange them as a 2xN matrix and feed a window from this matrix as input to ...
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152 views

Correlation of words and score

Say I have two fields: "Comments" (type text) and "Score" (type float, from 0 to 5) Sample data like: "I appreciate this ...