tkm | Topic Keyword Model is a novel topic model | Topic Modeling library
kandi X-RAY | tkm Summary
kandi X-RAY | tkm Summary
The Topic Keyword Model is a novel topic model that works quite differently from LDA from Blei et al. and other topic models. Please check and cite our paper: Johannes Schneider, Michail Vlachos. Topic Modeling based on Keywords and Context, SIAM International Conference on Data Mining (SDM), 2018.
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Top functions reviewed by kandi - BETA
- Run the optimizer
- Compute the keyword score based on the topic - word distribution
- Calculate the unique topic entropy
- Compute the topics for each document
- Convert a list of NDArray to a NumPy array
- Calculate one - step probability distribution
- Compute the perplexity of a matrix
- Process a corpus
- Convert a list of document ids to word ids
- Tokenize a docstring
- Convert a document into a list of words
- Prints a list of topics
- Compute the keyword score for the last iteration
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Community Discussions
Trending Discussions on tkm
QUESTION
I have .json file, but because its too big I will only paste part of it:
...ANSWER
Answered 2022-Mar-30 at 15:55Instead of replacing the translations dictionary each time, merge them using the update()
method.
QUESTION
I have .json file like this:
...ANSWER
Answered 2022-Mar-30 at 10:29I would suggest you keep the country codes in a dict format. This way you can easily access the underlying data. Note, this only works if all countries have a unique country code. With opening a file you should use the with statement so python closes the file automatically and not damage data.
QUESTION
I have a dataset with about 50 columns (all indicators I got from World Bank), Country Code and Year. These 50 columns are not all complete, and I would like to fill in the missing values based on an lm fit for the column for that specific country. For example:
Doing this for a single country and a single column is absolutely fine when following these steps here: Filling NA using linear regression in R
However, I have over 180 different countries I want to do this to. And I want this to work for each indicator per country (so 50 columns total) So in a way, each country and each column would have its own linear regression model that fills out the missing values.
Here is how it looked after I did the steps above: This is the expected output for ONE column. I would like to do this for EVERY column by individual country groups.
However, the data looks like this:
There are numerous countries and columns that I want to perform this on just like the post above.
This is for a project I am working on for my data-mining / statistics class. Any help would be appreciated and thanks so much in advance!
EDIT
I tried this:
...ANSWER
Answered 2021-Dec-02 at 13:40Since you already know how to do this for one dataframe with a single country, you are very close to your solution. But to make this easy on yourself, you need to do a few things.
Create a reproducible example using dput. The
janitor
library has the clean_names() function to fix columns names.Write your own interpolation function that takes a dataframe with one country as the input, and returns an interpolated dataframe for one country.
Pivot_longer to get all the data columns into a one parameterized column.
Use the
dplyr
function group_split to take your large multicountry dataframe, and break it into a list of dataframes, one for each country and parameter.Use the
purrr
function map to map each of the dataframes in the list to a new list of interpolate dataframes.Use dplyr's bind_rows to convert the list interpolated dataframes back into one dataframe, and pivot_wider to get your original data shape back.
QUESTION
I have to upload one file in different places on the web using katalon
I am using:
'Upload test-photo.png to input_browse'
...ANSWER
Answered 2021-Oct-22 at 12:27The purpose of writing keywords is code reusability - you can use the same code multiple times but with different parameters.
You could use something like this:
QUESTION
I wrote a script to import the characterization factors of the LCIA method EF 3.0 (adapated) on Brightway. I think it works fine as I see the right characterization factors on the Activity Browser (ex for the Climate Change method : but when I run calculations with the method, the results are not the same as on Simapro (where I got the CSV Import File from) : And for instance the result is 0 for the Climate Change method. Do you know what can be the issue ? It seems that the units are different but it is the same for the other methods that are available on Brightway.
Besides, I saw on another question that there would be a method implemented to import the EF 3.0 method, is it available yet ? Thank you very much for your help.
Code of the importation script :
...ANSWER
Answered 2021-Sep-01 at 15:29In LCA there's no agreement on elementary flows and archetypical emission scenarios / context (https://doi.org/10.1007/s11367-017-1354-3), and implementations of the impact assessment methods differ (https://www.lifecycleinitiative.org/portfolio_category/lcia/).
It is not unusual that the same activity and same impact assessment method returns different results in different software. There are some attempts to improve the current practices (see e.g , https://github.com/USEPA/LCIAformatter).
QUESTION
I am using Synth() package (see ftp://cran.r-project.org/pub/R/web/packages/Synth/Synth.pdf) in R.
This is a part of my data frame:
...ANSWER
Answered 2021-Aug-18 at 06:32I cannot tell you what's going on behind the scenes, but I think that Synth wants a few things:
First, turn factor variables into characters;
QUESTION
I am trying to remove a few letters after a special character (either :
or -
).
I have tried things like this but the result is not satisfactory:
...ANSWER
Answered 2021-Aug-10 at 13:14You can use -
QUESTION
when i use tkinter button i get the results i want though i'm using tkinter button from tkmacosx library as it supports background color. The problem is when i replace normal button with tkmacosx button they appear like dots.
...ANSWER
Answered 2021-May-04 at 16:20you need to increase number of pixels width= 200, height = 100
QUESTION
Here is my sample data:
...ANSWER
Answered 2021-Apr-28 at 19:59If the value of 'Yes' have any indication, then get the cumulative sum based on creating a logical vector with 'Yes' and use that as a grouping variable and create the 'nearest' as the first
value of 'iso3c'
QUESTION
i need to flat the object values in javascript . the ent is the input array . the first object the language consist of array of array values i need to flat the object value .[[{}],[{}],[{}]]
experted the value to be language: [{},{},{}];
...ANSWER
Answered 2020-Dec-25 at 13:27You can use destructuring to only select specific properties, and then .flat only the languages array.
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You can use tkm like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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