Questions tagged [interpolation]
Interpolation is a set of methods to construct intermediate points between known points.
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Interpolating missing data given county and state totals
Problem:
I have population data for states and their constituent counties over several years. Each row is uniquely identified by a state/county and a year. There are four population columns: ...
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Understanding the working of 'Interpolation'
'Interpolation' is a technique that is used to predict a null/empty value by studying its neighbouring points.
Interpolation doesn't take into consideration the entire dataset when predicting the ...
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Interpolation techniques predicting negative values in a column with positive values
I tried different interpolation techniques & for some numeric columns with only positive values the interpolation techniques: Polynomial, Cubic Spline & Radial Basis are predicting negative ...
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Mean Average Precision with 11 points interpolation method Python libs
I want to calculate mAP with 11 points interpolation method for object detection, as described here:
https://learnopencv.com/mean-average-precision-map-object-detection-model-evaluation-metric/
What ...
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What approaches can I take to reconstruct missing climate data?
I have climate datasets consisting of tables where each row has four elements: latitude, longitude, rainfall, and timestamp. This dataset covers the entirety of the planet. However this dataset is ...
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How to mathematically calculate individual pixel values after each image rotation?
If I have an image that is being rotated using OpenCV in python, about its centre, How do I mathematically calculate the pixel values after each rotation?
A python code for this operation would be ...
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Interpolate a point in time for two given geolocations and their times in python
Let's say I have two geolocations at given times. How can I interpolate these two geolocation and find any location for a given time time3 in python?
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what exactly is the "order"-parameter in pandas interpolation?
what exactly is the "order"-parameter in pandas interpolation?
it is mentioned in the doc:
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how many rows does pandas' interpolate consider? [closed]
How does pandas' DataFrame.interpolate() work in relation to the amount of rows it considers:
is it just the row before the NaNs and the row right after?
Or is it the whole DataFrame (how does that ...
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How to impute the missing values in time series for long periods
I have electrical consumption data between 2016-2019. The data was recorded every 30 minutes for 4 years. There is no data between 13/03/2019 - 31/03/209. I started with ...
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How often may algorithms improve on the quality of input data? Or i.e. extrapolate in information?
How often may algorithms improve on the quality of input data? Or i.e. extrapolate in information?
I've sometimes thought that it might seem like it's possible to "add data points" by some ...
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Find the best interpolation method for missing observations
I have a database which has measurements of objects every day every hour.
However, some data is missing and I don't have measurements for all the hours.
in order to get over this challenge I have ...
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Chossing between regression models
This is the first time I attempt to use machine learning with Keras. In contrast to others I need to use one of the disadvantage of such algorithms.
I need a ...
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empty fields to be filled with previous values
In the above sample data, I have empty fields and now the task is to fill the fields with previous values.
my columns are dates and the values are a number of items present for that particular article ...
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Is it possible retrive hourly data from daily weather data?
I'm a beginner, so sorry if my question could be basic. Reading on internet I've found example written in python that makes the reverse of my questions (covert from daily to monthly).
My problem is ...
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What is and how to calculate quartic interpolation?
I was reading the gist on the reward function used in OpenAI Five, but I didn't understand the way they calculate health's reward.
This is what they state: Hero health is scored according to a ...
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How to understand the return values of scipy.interpolate.splrep
Background
Continuation of Spline interpolation - why cube with 2nd derivative
as following Cubic Spline Interpolation in youtube. The example in the youtube is below.
Implemented using scipy....
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Regression of discrete continuous averaged data
If I have data that is continuous and discrete that is the average of a timestep. For example average power usage over the past 1 hour that is continually sampled every hour. How could I turn such ...
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Ordering scrambled 1D data sets by continuity
This is a cute little clustering problem that was probably solved a million times over, but I couldn't find a good reference for it.
I have 20 1D datasets with 400 entries each. In the picture they ...
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Sparse Data Interpolation
I have a price data set where on some days there are up to five data points and some days none at all. For example:
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Interpolation in nlp - definition of O term
Reading definition of interpolation below how are the O terms defined? Is this a value that is set manually?
Example
P( Sam | I am ) = count( Sam I am ) / count(I am) = 1 / 2
Interpolation using N-...
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Does it make sense to interpolate image just before a CNN?
I'm training a CNN with images which have lots of horizontal black lines (due to the nature of the sensor). I'm thinking in removing this artifacts by some kind of preprocessing (interpolation, median ...
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Neural net layer that preserves spatial information
I'm attempting to use a neural network as a kind of interpolator for a high-dimensional function.
We're doing this to circumvent the need for a physical model that calculates this function exactly, ...
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How to mask or crop IDW results
My question is: how can I mask or crop the results, using R, of IDW interpolation to only the area containing the original set of data points?
In the example below, 20 random points are used to ...
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Geometric weighting of temperature
I have a number of weather stations, and I know their positions. I would like to interpolate measurements from them for various other positions as a weighted average of these stations, but of course I ...
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