Questions tagged [numerical]
The numerical tag has no usage guidance.
33
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Questions regarding backward propagation
I am reading article regarding backward propagation https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/ . Lets say if I follow the example in the article but using only 3 node, ...
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Likelihood function of a Beta-Normal distribution
I'm going over a paper regarding the calculation of credit scoring By Kalkbrener and Onwunta. In the article, they derive the following Likelihood function, in order to find the MLE for $R^2$:
(...
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Calculating an integral with as few grid points as possible
Suppose I have a function $f\colon [0,1] \to \mathbb{R}$ which is maybe continuous (it's at least in $L^1$).
I have a sample of $N$ points $\{x_i\}$ taken from the domain $[0,1]$ randomly from some ...
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Converting categorical to the percentage
How do I convert the categorical value to the percentage?|
I have this asset wellness data:
Poor: 3
Warning: 27
Good: 120
How do I convert it to the percentage ...
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Numerical instabilety with kmeans
If i understand the math right a kmeans iteration should always improve cosine similarity. So if the data is z-normalized it should always improve corelation
Well it seemed to be the case for a small ...
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Binary transformer classification model predicts everything as same value
I'm training a binary classifier using a transformer on structured numerical data (so the order of the columns in my spreadsheet matters). I have adapted the keras text classification model for IMDb ...
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Clustering mixed type variables with Orange
I wonder if with Orange it is possible to cluster mixed type data, so a dataset with numeric as well as discrete (categorical) data (ordered / unordered). Can you show an example of how that could be ...
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Why is Orange (CSV import or Line Series) doing some weird rounding on my data?
The data I have is in tab-separated format (exported from MetaTrader5):
...
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Dealing with little available data: transfer learning
Suppose I seek to predict a certain numerical value, whereby the data set which contains the predetermined correct labels is only very small. However, I'm also provided a large data set with a label ...
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Over-sampling when predicting a contionuous variable
Lets say i am predicting house selling prices (continuous) and therefore have multiple independent variables (numerical and categorical). Is it common practice to balance the dataset when the ...
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Separating numerical and categorical features in a binary classification problem
I have a dataset with employee data with around 9500 rows, and have to predict if the target is 0 or 1.
Some of my features are the department of an employee, gender, salary, review_score(numerical),...
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With a 5000x20 CSV as data input discover the most common occurrences of numbers in a row
As input I have a CSV with 5000 lines (and growing) and 20 fixed columns containing a number from 1-80.
A row may look like this.
Is it possible using Orange3 to analyze each row and find out what ...
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976
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Separate discrete and continuous variables
I know how to separate numerical and categorical data as follows:
...
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6k
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Separate numerical and categorical variables
I have a dataset (42000, 10) which contains 7 categorical features and 3 numerical. I would like to separate both the numerical and categorical features into 2 different data frames i.e I would like 2 ...
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3
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178
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Transforming Categorical to Numerical variable
I have a categorical variable with 4 levels ('8 c', '6 c','NAN','Others') and I want to convert it to numerical form. an Obvious way is to simply remove the 'c' part from the first two categories and ...
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Problem with binning
I am trying to change continuous data points to categorical by using binning. I know two techniques, i) equal width bins ii) bins with equal number of elements.
My questions are:
Which type of ...
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partial numerical array - pattern matching
I have a linear numerical array source and I want to find/match test array as pattern :
...
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1
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5 digit number mis-reads analysis
Nothing to do with number recognition in the classical 'hand-written' sense
Disclaimer above to avoid this being counted as a repeat.
I have a selection of 96 serial numbers, and a separate ...
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Purpose of converting continuous data to categorical data
I was reading through a notebook tutorial working with the Titanic dataset, linked here, and noticed that they highly favored ordinal data to continuous data.
For example, they converted both the Age ...
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346
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Cluster method with binary variable
I need to do a cluster analysis for the following variables:
...
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1
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What is the intuition behind using Monte Carlo to solve a differential equation
Conceptually, I understand how a numerical method like Monte Carlo is used to solve a definite integral. Because integral of a function is the area bounded by the curve, the ratio of random points ...
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How to do non arithmetic operation in python 3 [closed]
lets say a=3 b=4 and c is an unknown constant.
a=3
b=4
F=0
F=a*b*c
print(F)
Its an error. I want 12*c or 12c
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1
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MinMaxScaler returned values greater than one
Basically I was looking for a normalization function part of sklearn, which is useful later for logistic regression.
Since I have negative values, I chose MinMaxScaler with: ...
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Convert nominal to numeric variables?
I am trying to develeop an algorithm with sklearn and Tensorflow to predict which car can be offer to each customer.
To do that I have a database with the answers of one survey to 1000 customers.
An ...
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1
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Replacing words by numbers in multiple columns of a data frame in R
I want to replace the values in a data set (sample in the picture) using numbers instead of words, e.g., 1 instead of D, ...
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Homemade deep learning library: numerical issue with relu activation
For the sake of learning the finer details of a deep learning neural network, I have coded my own library with everything (optimizer, layers, activations, cost function) homemade.
It seems to work ...
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1
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What are the advantages or disadvantages of Owl?
Owl is the numerical library for OCaml: https://github.com/ryanrhymes/owl
It is supposed to be an equivalent of numpy and also have capabilities of tensorflow.
Any insights on why it should be used ...
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How to choose the optimal k in k-protoypes?
To analyze a dataset from banking I have both numerical and categorical values. I transform them to analyze with k-prototypes.
The original dataset:
The modified dataset:
E.g.: Job (for 1 to 12 '...
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1
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Do numerical inaccuracies play any role in training neural networks?
Are there publications which mention numerical problems in neural network optimization?
(Blog posts, articles, workshop notes, lecture notes, books - anything?)
Background of the question
I've ...
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6
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37k
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Encoding features like month and hour as categorial or numeric?
Is it better to encode features like month and hour as factor or numeric in a machine learning model?
On the one hand, I feel numeric encoding might be reasonable, because time is a forward ...
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1
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How to estimate the mutual information numerically?
Suppose I have a sample {$z_i$}$_{i\in[0,N]}$ = {($x_i,y_i$)}$_{i\in[0,N]}$ which commes from a probability distribution $p_z(z)$. How can I use it to estimate the mutual information between X and Y ?
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How can I dynamically distinguish between categorical data and numerical data?
I know someone who is working on a project that involves ingesting files of data without regard to the columns or data types. The task is to take a file with any number of columns and various data ...
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Steps in exploratory methods for mild-sized data with mixed categorical and numerical values?
Experienced in signal/image analysis, and new to data science, I recently was challenged with a relatively simple dataset: 100 to 200 items, about 10-20 numerical variables (in the [0-1] or percentage ...
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