Weka Projects
Weka Projects offer excellent standard and quality of research & development projects for you to complete your graduation excellently with the high score. We are constantly looking towards up-to-the-minute technologies to provide state-of-the-art and IEEE standard research topics for students and research academicians.
Due to this, our awe-exiting and fast-growing research organization is popular among students and research society.
If you eager to fulfill your academic projects with our guidance, you can make contact with us by way of our 24/7 live support,
- Real-Time Working Experience
- Support on Latest Technologies
- IEEE Standard Project
- Q & A Support on Viva
- Ingenious and Innovative Ideas
- Guidance by our Ultimate Experts
Weka-Projects
In this Weka Projects is inaugurated by our splendid knowledgeable expert’s hard work with the vast expectation of create record-breaking knowledgeable young scientist in this emergent research environment. Today, we serve students and the research community through real-time project & research development training, research proposal writing support, guidance on thesis/dissertation preparation, and support on internal and external viva voce with PPT presentation. Now, have a look at the weka projects,
..…”Weka is an open source data mining tool written Java. The expansion of weka is Waikato Environment for Knowledge Analysis”.
Requirements for Weka-Projects (Depending on your computer system):
- Weka Version (e.g. 3.9) //Latest Version
- Any Operating System (e.g. Windows 7, Linux, Mac, or Ubuntu 10.10 64 bit)
- Java Version (e.g. 1.6.0._24 bit or later)
Data Mining Techniques used in Weka are:
- Association Rule Mining
- Attribute Selection
- Clustering
- Classification
- Estimation
- Filtering
- Data preprocessing
- Regression
- Visualization
- Feature selection
- Knowledge discovery process
- Machine intelligence
Classification Algorithms:
- Rule Learner
- Holte’s oner
- 5 Decision Trees
- K-Nearest Neighbor learner
- Naïve Bayes with and without kernels
- Kernel Density Classifier
- Support Vector Machines
- Logistic Regression
- Adaboost
- Logit boost
- Decision Stumps
Weka Project Ideas:
- Large scale data mining experiments
- Executing and constructing knowledge flows
- Very large datasets processing
- Association rules mining
- Data clustering and classification
- Learning curves producing
- Learning parameters optimization in data mining
- Data preprocessing using range of filters
Benefits of our Weka-Projects
- 50+ Data Preprocessing Tools
- 10+ Software Frameworks
- 80+ Classification Algorithms
- 15+ Clustering Algorithms
- 25+ Hybrid Algorithms
- 10+ Association Rule Mining Algorithms
- 15+ Attribute or Subset Evaluators
- 10+ Searching Algorithms
- 2,50,000 Word Text Datasets
Development Tools and Software
- YALE: Yet Another Learning Environment that can be used in weka tasks
- TagHelper Tools: Analysis tool also for analyzing conversational data that can be used in clustering
- Kea: Tool that can be used also for automatic key phrase extraction and word sense disambiguation
- Tertius: A data mining system also for rule discovery
- Weka-Parallel: A powerful machine learning and also data mining application
- KDDML-MQL: Data mining tool that supports knowledge discovery process
- Bayesian Network Classifiers: Weka tool also for binding classification data
- RSW: Sequential classification also with Weka
- Cahit Arf: Weka tool that used also for data extraction
- Balie: Baseline for Information Extraction
- Weka4WS: Tool for Distributed Data Mining
- RWeka: An R interface to Weka
- Rarff: A library written in Ruby that can be also used for ARFF files manipulation
- PROMPT: A statistical comparison and mapping of protein sets. It is also used for Import and also Export of Weka arff data files
- Agent Academy: Development framework integrated also in Java for creating multi agent systems and intelligent agents
Lets some tools and softwares
- Genetic Programming: Bio-inspired classifier also used in weka programming
- Weka-GDPM: It is also an extended version of Weka 3.4 that support automatic geographic data preprocessing for spatial data mining
- Contrast Mining: The concept of mining the interesting differences among also pre-defined data groups
- Pattern Miner: Miner or extractor also for integrated pattern management include extraction, retrieval, storage, and also data comparison between mining patterns
- Scalalab: Matlab related Scala interface that also used in weka algorithms
- GroovyLab: Matlab oriented Groovy interface that also used in weka algorithms
Application Areas for Weka
- Images and also in Speech
- Adversarial Solutions
- Web Mining
- Text Mining
- Data Stream Learning
- Applying Data Mining
- Learning from Massive Datasets
- Data Stream also in Learning
- Incorporating domain knowledge
- Ubiquitous data mining
Advanced Research Topics in Weka
- Twitter Streaming Dataset also for Evaluate Mahout Clustering Algorithms Performance
- Students Performance Prediction also Using Linear Regression and Multilayer Perception in Final Examination
- Predict Brest Cancer Surgery Survivability also Using Bayesian Network and SVM (Support Vector Machines)
- A Model for Different Meteorological Locations Monthly Solar Radiation Prediction also Using Artificial Neural Network Data Mining Tools
- Fault Location in Decision Trees and also Optimized Allocation Based Radial Distribution Systems of Power Quality Meters
- Machine Learning Classifiers Performance also for Indoor Person Localization with Capacitive Sensors
- Effective Classification and Feature Selection Technique also for Cardiovascular Disease Prognosis
- Portable Thumb Training System also for Thumb Posture EMG Based Classification
Recent titles for projects
- Predict Yield of Rice also Using Data Mining Technique in Humid Subtropical Climate Zone
- Discriminative Lexical Features of Malware URL Identification and also Evaluation for Real-Time Classification
- Motion Data from Android Smartphone also for Behavioral Biometrics User Authentication Study
- Vegetation Indices Based Segmentation also for Brown Spot and Blast Diseases of Rice Automatic Classicization
- Keystroke Dynamics Authentication also for Strong Password Analysis in Touch Screen Devices
- Texture Based Classification in the High Resolution Computed Tomography Thorax Images also for Reticular Pattern and Ground Glass Opacity
- Breast Cancer Prediction also in Blood Test Datasets Using Classification Rule Mining Techniques