Showing 14 open source projects for "number prediction algorithm"

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  • 1
    tsfresh

    tsfresh

    Automatic extraction of relevant features from time series

    tsfresh is a python package. It automatically calculates a large number of time series characteristics, the so called features. tsfresh is used to to extract characteristics from time series. Without tsfresh, you would have to calculate all characteristics by hand. With tsfresh this process is automated and all your features can be calculated automatically. Further tsfresh is compatible with pythons pandas and scikit-learn APIs, two important packages for Data Science endeavours in python....
    Downloads: 0 This Week
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  • 2
    UMAP.jl

    UMAP.jl

    Uniform Manifold Approximation and Projection (UMAP) implementation

    A pure Julia implementation of the Uniform Manifold Approximation and Projection dimension reduction algorithm. The umap function takes two arguments, X (a column-major matrix of shape (n_features, n_samples)), n_components (the number of dimensions in the output embedding), and various keyword arguments.
    Downloads: 0 This Week
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  • 3
    Roots.jl

    Roots.jl

    Root finding functions for Julia

    ...For functions where a bracketing interval is known (one where f(a) and f(b) have alternate signs), a bracketing method, like Bisection, can be specified. The default is Bisection, for most floating point number types, employed in a manner exploiting floating point storage conventions. For other number types (e.g. BigFloat), an algorithm of Alefeld, Potra, and Shi is used by default. These default methods are guaranteed to converge. Other bracketing methods are available.
    Downloads: 0 This Week
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  • 4
    Go Recipes

    Go Recipes

    Collection of handy tools for Go projects

    ...This helps to identify code areas with high and low coverage. Useful when you have a large project with lots of files and packages. This 2D image-hash of your project should be more representative than a single number. For each module, the node representing the greatest version (i.e., the version chosen by Go's minimal version selection algorithm) is colored green. Other nodes, which aren't in the final build list, are colored grey — by the official Go team. Use to find unexpected dependencies or visualize the project. Works best for a small number of packages, for large projects use grep to narrow down subgraph. ...
    Downloads: 0 This Week
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  • 5
    NannyML

    NannyML

    Detecting silent model failure. NannyML estimates performance

    ...By using NannyML, data scientists can finally maintain complete visibility and trust in their deployed machine learning models. When the actual outcome of your deployed prediction models is delayed, or even when post-deployment target labels are completely absent, you can use NannyML's CBPE-algorithm to estimate model performance.
    Downloads: 0 This Week
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  • 6
    Bayesian Optimization

    Bayesian Optimization

    Python implementation of global optimization with gaussian processes

    This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic...
    Downloads: 0 This Week
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  • 7
    Open Source Data Quality and Profiling

    Open Source Data Quality and Profiling

    World's first open source data quality & data preparation project

    This project is dedicated to open source data quality and data preparation solutions. Data Quality includes profiling, filtering, governance, similarity check, data enrichment alteration, real time alerting, basket analysis, bubble chart Warehouse validation, single customer view etc. defined by Strategy. This tool is developing high performance integrated data management platform which will seamlessly do Data Integration, Data Profiling, Data Quality, Data Preparation, Dummy Data...
    Downloads: 1 This Week
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  • 8
    DISTOD

    DISTOD

    Distributed discovery of bidirectional order dependencies

    The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table.
    Downloads: 0 This Week
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  • 9
    Cubature.jl

    Cubature.jl

    One- and multi-dimensional adaptive integration routines for Julia

    This module provides one- and multi-dimensional adaptive integration routines for the Julia language, including support for vector-valued integrands and facilitation of parallel evaluation of integrands, based on the Cubature Package by Steven G. Johnson. Adaptive integration works by evaluating the integrand at more and more points until the integrand converges to a specified tolerance (with the error estimated by comparing integral estimates with different numbers of points). The Cubature...
    Downloads: 0 This Week
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  • 10
    AI learning

    AI learning

    AiLearning, data analysis plus machine learning practice

    We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community,...
    Downloads: 0 This Week
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  • 11

    Random Bits Forest

    RBF: a Strong Classifier/Regressor for Big Data

    We present a classification and regression algorithm called Random Bits Forest (RBF). RBF integrates neural network (for depth), boosting (for wideness) and random forest (for accuracy). It first generates and selects ~10,000 small three-layer threshold random neural networks as basis by gradient boosting scheme. These binary basis are then feed into a modified random forest algorithm to obtain predictions. In conclusion, RBF is a novel framework that performs strongly especially on data...
    Downloads: 2 This Week
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  • 12
    SmartRoot

    SmartRoot

    Semi-automated root image analysis software

    SmartRoot is a semi-automated image analysis software which streamlines the quantification of root growth and architecture for complex root systems. The software combines a vectorial representation of root objects with a powerful tracing algorithm which accommodates to a wide range of image source and quality. The software supports a sampling-based analysis of root system images, in which detailed information is collected on a limited number of roots selected by the user according to specific research requirements. SmartRoot is an operating system independent freeware based on ImageJ and uses cross-platform standards (XML, SQL, Java) for communication with data analysis softwares. ...
    Downloads: 5 This Week
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  • 13
    Visualization of Protein-Ligand Graphs

    Visualization of Protein-Ligand Graphs

    Compute protein graphs. Moved to https://github.com/MolBIFFM/PTGLtools

    NOTE: Project moved to https://github.com/MolBIFFM/PTGLtools. The Visualization of Protein-Ligand Graphs (VPLG) software package computes and visualizes protein graphs. It works on the super-secondary structure level and uses the atom coordinates from PDB files and the SSE assignments of the DSSP algorithm. VPLG is command line software. If you do not like typing commands, try our PTGL web server: http://ptgl.uni-frankfurt.de/
    Downloads: 0 This Week
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  • 14
    ChEnMTD

    ChEnMTD

    Calculate the number of theoretical trays with McCabe-Thiele method

    Use the McCabe-Thiele method to calculate the number of theoretical trays in a distillation column operated under the conditions specified. It has tools for data analysis to obtain empirical or semi-empirical equilibrium models. You can even use cubic splines. This project uses icons of "Open Icon Library" https://sourceforge.net/projects/openiconlibrary/
    Downloads: 0 This Week
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