Kalvar Lin
16pods
Machine Learning (マシンラーニング) in this project, it implemented multi-perceptrons neural network (ニューラルネットワーク) and it named Back Propagation Neural Network (BPN).It is designed unlimited hidden layers to do the training tasks and also prepared flexible spaces to wait for combining Fuzzy theory in network. This network can be used in products recommendation (おすすめの商品), user behavior analysis (ユーザーの行動分析), data mining (データマイニング) and data analysis (データ分析).
License: MIT
KRBeaconFinder can lazy scanning beacons, relax using CoreLocation to monitor beacon-regions or use CoreBluetooth (BLE) to scan. And auto pop-up the message to notify users when they locked on the screen. It also can simulate beacon adversting from peripheral adversting.
License: MIT
KRBle implements the Bluetooth Low Engery (BLE) and simulate SPP transfer big data ( ex : image / 2,000 words ), central and peripheral can exchange the big data to each other, summarized, you could easy use this project to build your BLE applications.
License: MIT
Machine Learning (マシンラーニング) in this project, it implemented 3 layers ( Input Layer, Hidden Layer and Output Layer ) neural network (ニューラルネットワーク) and implemented Back Propagation Neural Network (BPN), QuickProp theory and Kecman's theory (EDBD). KRBPN can be used in products recommendation (おすすめの商品), user behavior analysis (ユーザーの行動分析), data mining (データマイニング) and data analysis (データ分析).
License: MIT
It still works in recommendation system and real-time user behavior analysis on mobile apps.
License: MIT
KRDragView simulates dragging and sliding the view to show the menu under background. Like the cards, you could drag the view and release it to move/ show something under itself.
License: MIT
KRFuzzyCMeans has implemented Fuzzy C-Means (FCM) the fuzzy (ファジー理論) clustering / classification algorithm (クラスタリング分類) in Machine Learning (マシンラーニング). It could be used in data mining (データマイニング) and image compression (画像圧縮).
License: MIT
Machine Learning (マシンラーニング) in this project, it implemented the Grey Theory. This theory could use in big data analysis (データ分析), user behavior analysis (ユーザーの行動分析) and data mining (データマイニング) as well, especially find out what sub-factories impact on the real results via big data.
License: MIT
KRHebbian implemented Hebbian algorithm that is a non-supervisor of self-organization algorithm of Machine Learning (自分学習アルゴリズム).
License: MIT
KRImageViewer could let you easy browse photos from the URLs, storage or folders. You can scroll to change page, pinching zooming, dragging and swiping to close, this viewer supports automatic rotation.
License: MIT
KRKmeans has implemented K-Means the clustering algorithm (クラスタリング分類) and achieved multi-dimensional clustering in this project. KRKmeans could be used in data mining (データマイニング), image compression (画像圧縮) and classification.
License: MIT
Machine Learning (マシンラーニング) in this project, it implemented KNN(k-Nearest Neighbor) that classification method. It can be used on products recommendation (おすすめの商品), user behavior analysis (ユーザーの行動分析), data mining (データマイニング) and data analysis (データ分析).
License: MIT
Machine Learning (マシンラーニング) in this project, it implemented multi-layer perceptrons neural network (ニューラルネットワーク) and Back Propagation Neural Network (BPN). It designed unlimited hidden layers to do the training tasks. This network can be used in products recommendation (おすすめの商品), user behavior analysis (ユーザーの行動分析), data mining (データマイニング) and data analysis (データ分析).
License: MIT
KRRBFNN is a Radial basis function network used Guassian function, implemented OLS, LMS, SGA, Random algorithms.
License: MIT
KRSVM is implemented Support Vector Machine (SVM) of machine learning, it current achieved SMO and RBF, Tangent, Linear these 3 kernel functions to do predication.
License: MIT
KRHebbian is a self-learning algorithm (adjust the weights) in neural network of Machine Learning (自分学習アルゴリズム).
License: MIT