Questions tagged [numerical]
The numerical tag has no usage guidance.
33
questions
0
votes
0
answers
10
views
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, ...
0
votes
1
answer
52
views
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 $R^2$:
(...
1
vote
0
answers
20
views
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 ...
0
votes
1
answer
20
views
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 ...
0
votes
0
answers
14
views
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 ...
0
votes
0
answers
133
views
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 ...
0
votes
0
answers
64
views
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 ...
1
vote
0
answers
33
views
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):
...
1
vote
0
answers
13
views
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 ...
0
votes
1
answer
38
views
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 ...
0
votes
1
answer
152
views
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),...
1
vote
0
answers
28
views
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 ...
2
votes
0
answers
976
views
Separate discrete and continuous variables
I know how to separate numerical and categorical data as follows:
...
0
votes
1
answer
6k
views
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 ...
0
votes
3
answers
178
views
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 ...
0
votes
1
answer
258
views
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 ...
1
vote
1
answer
27
views
partial numerical array - pattern matching
I have a linear numerical array source and I want to find/match test array as pattern :
...
2
votes
1
answer
70
views
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 ...
3
votes
3
answers
7k
views
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 ...
0
votes
0
answers
346
views
Cluster method with binary variable
I need to do a cluster analysis for the following variables:
...
2
votes
1
answer
69
views
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 ...
1
vote
0
answers
17
views
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
1
vote
1
answer
7k
views
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: ...
0
votes
1
answer
932
views
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 ...
2
votes
1
answer
12k
views
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, ...
1
vote
2
answers
176
views
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 ...
-1
votes
1
answer
548
views
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 ...
2
votes
0
answers
1k
views
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 '...
4
votes
1
answer
1k
views
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 ...
44
votes
6
answers
37k
views
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 ...
6
votes
1
answer
2k
views
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 ?
...
14
votes
3
answers
8k
views
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 ...
3
votes
1
answer
202
views
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 ...