ベスト 19 の無料データ マイニング ツール

今日の世界ではデータはお金であると言ったのは当然のことです。アプリベースの世界への移行に伴い、データが指数関数的に増加しています。ただし、ほとんどのデータは構造化されていないため、データから有用な情報を抽出し、理解可能で使用可能な形式に変換するには、プロセスと方法が必要です。

データ マイニングまたは「データベースでの知識発見」は、人工知能、機械学習、統計、およびデータベース システムを使用して、大規模なデータ セットからパターンを発見するプロセスです。

無料のデータ マイニング ツール は、Knime や Orange などの完全なモデル開発環境から、Java、C++、そしてほとんどの場合 Python で書かれたさまざまなライブラリにまで及びます。通常、データ マイニングに関連する 4 種類のタスクがあります。

1. 分類:使い慣れた構造を一般化して新しいデータに適用するタスク
2. クラスタリング:データ内の注目された構造を使用せずに、何らかの形で同じであるデータ内のグループと構造を見つけるタスク。
3. アソシエーション ルールの学習:変数間の関係を探す
4. 回帰:わずかな誤差でデータをモデル化する関数を見つけることを目指します。

データ マイニング用のフリー ソフトウェア ツールのリスト –

2022 年の最高の無料データ マイニング ツール リスト:-

1.ラピッドマイナー –

以前は YALE (Yet another Learning Environment) と呼ばれていた Rapid Miner は、研究と実際のデータ マイニング タスクの両方に利用される、機械学習とデータ マイニングの実験のための環境です。 .これは間違いなく、世界をリードするデータ マイニング用のオープン ソース システムです。 Java プログラミング言語で書かれたこのツールは、テンプレートベースのフレームワークを通じて高度な分析を提供します。

これにより、XML ファイルに詳述され、Rapid Miner のグラフィカル ユーザー インターフェイスで作成された、任意にネスト可能な膨大な数の演算子で実験を構成できます。一番いいのは、ユーザーがコードを書く必要がないことです。データを簡単に分析できる多くのテンプレートやその他のツールが既に用意されています。

2. IBM SPSS モデラー –

IBM SPSS Modeler ツール ワークベンチは、テキスト分析などの大規模なプロジェクトでの作業に最適であり、そのビジュアル インターフェイスは非常に価値があります。プログラミングなしで、さまざまなデータ マイニング アルゴリズムを生成できます。また、異常検出、ベイジアン ネットワーク、CARMA、Cox 回帰、および逆伝播学習による多層パーセプトロンを使用する基本的なニューラル ネットワークにも使用できます。気弱な人向けではありません。

3.オラクルのデータマイニング –

データ マイニング分野のもう 1 つの大物は Oracle です。 As part of their Advanced Analytics Database option, Oracle data mining allows its users to discover insights, make predictions and leverage their Oracle data. You can build models to discover customer behavior target best customers and develop profiles.

The Oracle Data Miner GUI enables data analysts, business analysts and data scientists to work with data inside a database using a rather elegant drag and drop solution. It can also create SQL and PL/SQL scripts for automation, scheduling and deployment throughout the enterprise.

4. Teradata –

Teradata recognizes the fact that, although big data is awesome, if you don’t actually know how to analyze and use it, it’s worthless. Imagine having millions upon millions of data points without the skills to query them. That’s where Teradata comes in. They provide end-to-end solutions and services in data warehousing, big data and analytics and marketing applications.

Teradata also offers a whole host of services including implementation, business consulting, training and support.

5. Framed Data –

It’s a fully managed solution which means you don’t need to do anything but sit back and wait for insights. Framed Data takes data from businesses and turns it into actionable insights and decisions. They train, optimize, and store product ionized models in their cloud and provide predictions through an API, eliminating infrastructure overhead. They provide dashboards and scenario analysis tools that tell you which company levers are driving metrics you care about.

6. Kaggle –

Kaggle is the world’s largest data science community. Companies and researchers post their data and statisticians and data miners from all over the world compete to produce the best models.

Kaggle is a platform for data science competitions. It help you solve difficult problems, recruit strong teams, and amplify the power of your data science talent.

3 steps of working –

1. Upload a prediction problem
2. Submit
3. Evaluate and Exchange

7. Weka –

WEKA is a very sophisticated best data mining tool. It shows you various relationships between the data sets, clusters, predictive modelling, visualization etc. There are a number of classifiers you can apply to get more insight into the data.

8. Rattle –

Rattle stands for the R Analytical Tool to Learn Easily. It presents statistical and visual summaries of data, transforms data into forms that can be readily modelled, builds both unsupervised and supervised models from the data, presents the performance of models graphically, and scores new datasets.

It is a free and open source best data mining toolkit written in the statistical language R using the Gnome graphical interface. It runs under GNU/Linux, Macintosh OS X, and MS/Windows.

9. KNIME –

Konstanz Information Miner is a user friendly, intelligible and comprehensive open-source data integration, processing, analysis and exploration platform. It has a graphical user interface which helps users to easily connect the nodes for data processing.

KNIME also integrates various components for machine learning and data mining through its modular data pipelining concept and has caught the eye of business intelligence and financial data analysis.

10. Python –

As a free and open source language, Python is most often compared to R for ease of use. Unlike R, Python’s learning curve tends to be so short it’s become legendary. Many users find that they can start building data sets and doing extremely complex affinity analysis in minutes. The most common business-use case-data visualizations are straightforward as long as you are comfortable with basic programming concepts like variables, data types, functions, conditionals and loops.

11. Orange –

Orange is a component based data mining and machine learning software suite written in Python Language. It is an Open Source data visualization and analysis for novice and experts. Data mining can be done through visual programming or Python scripting. It is also packed with features for data analytics, different visualizations, from scatterplots, bar charts, trees, to dendrograms, networks and heat maps.

12. SAS Data Mining –

Discover data set patterns using SAS Data Mining commercial software. Its descriptive and predictive modelling provides insights for better understanding of the data. They offer an easy to use GUI. They have automated tools from data processing, clustering to the end where you can find best results for taking right decisions. Being a commercial software it also includes advanced tools like Scalable processing, automation, intensive algorithms, modelling, data visualization and exploration etc.

13. Apache Mahout –

Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily in the areas of collaborative filtering, clustering and classification.

Apache Mahout supports mainly three use cases:Recommendation mining takes users’ behavior and from that tries to find items users might like. Clustering takes e.g. text documents and groups them into groups of topically related documents. Classification learns from existing categorized documents what documents of a specific category look like and is able to assign unlabeled documents to the (hopefully) correct category.

14. PSPP –

PSPP is a program for statistical analysis of sampled data. It has a graphical user interface and conventional command-line interface. It is written in C, uses GNU Scientific Library for its mathematical routines, and plot UTILS for generating graphs. It is a Free replacement for the proprietary program SPSS (from IBM) predict with confidence what will happen next so that you can make smarter decisions, solve problems and improve outcomes.

15. jHepWork –

jHepWork is a free and open-source data-analysis framework that is created as an attempt to make a data-analysis environment using open-source packages with a comprehensible user interface and to create a tool competitive to commercial programs.

JHepWork shows interactive 2D and 3D plots for data sets for better analysis. There are numerical scientific libraries and mathematical functions implemented in Java. jHepWork is based on a high-level programming language Jython, but Java coding can also be used to call jHepWork numerical and graphical libraries.

16. R programming Language–

There’s no mystery why R is the superstar of free data mining tools on this list. It’s free, open source and easy to pick up for people with little to no programming experience. There are literally thousands of libraries that can be incorporated into the R environment making it a powerful data mining environment. It’s a free software programming language and software environment for statistical computing and graphics.

The R language is widely used among data miners for developing statistical software and data analysis. Ease of use and extensibility has raised R’s popularity substantially in recent years.

17. Pentaho –

Pentaho provides a comprehensive platform for data integration, business analytics and big data. With this commercial tool you can easily blend data from any source. Get insights into your business data and make more accurate information driven decisions for future.

18. Tanagra –

TANAGRA is a data mining software for academic and research purposes. There are tools for exploratory data analysis, statistical learning, machine learning and databases area. Tanagra contains some supervised learning but  also other paradigms such as clustering, factorial analysis, parametric and non-parametric statistics, association rule, feature selection and construction algorithms.

19.  NLTK –

Natural Language Toolkit, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for the python language. It provides a pool of language processing tools including data mining, machine learning, data scrapping, sentiment analysis and other various language processing tasks. Build python programs to deal with human language data.

We hope our list of best free data mining tools was helpful to you. We would love to know your opinion, please do share your views in the comments section below.