price-prediction | Predicting different market prices | Predictive Analytics library

by x4nth055 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | price-prediction Summary

price-prediction is a Python library typically used in Analytics, Predictive Analytics, Neural Network applications. price-prediction has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository uses recurrent neural networks to predict the price of any stock, currency or cryptocurrency ( any market that yahoo_fin library supports ) using keras library.

Support

Quality

Security

License

Reuse

Support

price-prediction has a low active ecosystem.

It has 19 star(s) with 12 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

price-prediction has no issues reported. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of price-prediction is current.

Quality

price-prediction has 0 bugs and 0 code smells.

Security

price-prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

price-prediction code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

price-prediction is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

price-prediction releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed price-prediction and discovered the below as its top functions. This is intended to give you an instant insight into price-prediction implemented functionality, and help decide if they suit your requirements.

Train the model
Create a model
Create the model
Check if model exists
Plot the test set
Get test prices
Get the prediction of the model
Returns y value of y
Compute the accuracy
Calculate classified y_predices
Return the shifted y value
Predict price
Get the last price
Returns the mean absolute error
Compute the mean squared error

Get all kandi verified functions for this library.

price-prediction Key Features

No Key Features are available at this moment for price-prediction.

price-prediction Examples and Code Snippets

No Code Snippets are available at this moment for price-prediction.

Community Discussions

Trending Discussions on price-prediction

name 'Bidirectional' is not defined

How to predict a certain time span into the future with recurrent neural networks in Keras

Parsing a website with is not working with "fromestring" in python

How to get latitude and latitude for an address column in a dataframe using geopy?

Getting error (numpy.ndarray' object is not callable) while running following code in Jupyter

QUESTION

name 'Bidirectional' is not defined

Asked 2022-Mar-20 at 04:31

Im following this tutorial and right when I want to initialize a sequential keras, like the code below:

...

ANSWER

Answered 2022-Mar-20 at 04:31

You’re most likely missing the import statement from the tensorflow package.

It appears that’s there is a link to the source code in that article which shows the full import statement.

Source https://stackoverflow.com/questions/71543978

QUESTION

How to predict a certain time span into the future with recurrent neural networks in Keras

Asked 2021-Nov-09 at 10:12

I have the following code for time series predictions with RNNs and I would like to know whether for the testing I predict one day in advance:

...

ANSWER

Answered 2021-Nov-06 at 22:31

First, I suggest you read Tensorflow's tutorial on time series forecasting. I played around a bit with your code and the data provided. The first important thing is that only the temperature column contains information. In the code below, I prepare the data so that X over a time window of 96 samples/steps and the next step is in Y. X is of dimension (n_samples, 96, 1) and Y of dimension (n_samples, ), I use only steps_backwards points for the past (and discarded the future for simplicity, without affecting the generality) I have tried different models (a simple Fully Connected or RNN + FC, etc.). I'm doing mean pooling (with the functional API rather than the sequential model definition approach) so that I have a single predicted value at the end.

Source https://stackoverflow.com/questions/69808059

QUESTION

Parsing a website with is not working with "fromestring" in python

Asked 2021-Jul-28 at 14:39

I'm trying to retrieve data from a xml website through "fromstring" of xml.etree.ElementTree. The python code works fine for the test link: https://www.w3schools.com/xml/cd_catalog.xml, but it doesn't work for the link that we'll be using: https://griddata.elia.be/eliabecontrols.prod/interface/oneminuteimbalance/SystemImbalancePrice

I've double checked if the url is correct and it is. The content of both website seems to be read differently, would someone have some advice?

...

ANSWER

Answered 2021-Jul-28 at 14:39

The code below return a list of dicts. Not XML

Source https://stackoverflow.com/questions/68562106

QUESTION

How to get latitude and latitude for an address column in a dataframe using geopy?

Asked 2021-May-08 at 16:19

I am currently working on a kaggle dataset House price prediction

It has errors in the latitude and latitude column, so I decided to use geopy to get right values for those two columns.

And it works fine if I use it on one single address but returns None if applied on entire column.

...

ANSWER

Answered 2021-May-08 at 16:19

The problem is in the address of the dataset. If you use the below try catch code, you can see there are many wrong address in the dataset.

Source https://stackoverflow.com/questions/67448887

QUESTION

Getting error (numpy.ndarray' object is not callable) while running following code in Jupyter

Asked 2020-Aug-26 at 08:15

Checking Robustness of the model In this section we will check robustness of our LSTM model. I have used new unseen datasets for this from July 1, 2017 to July 20,2017. I have downloaded the data sets from google finance website to check for robustness of the model.

...

ANSWER

Answered 2020-Aug-26 at 08:15

The .values property shouldn't have ():

Source https://stackoverflow.com/questions/63593284

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install price-prediction

to use this repository, install required packages.
Python 3.6
keras==2.2.4
sklearn==0.20.2
numpy==1.16.2
pandas==0.23.4
matplotlib==2.2.3
yahoo_fin

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: