نتایج جستجو برای: parametric knn method in pilambara

تعداد نتایج: 17244768  

Journal: :Proceedings of the ... AAAI Conference on Artificial Intelligence 2023

Retrosynthesis, which predicts the reactants of a given target molecule, is an essential task for drug discovery. In recent years, machine learing based retrosynthesis methods have achieved promising results. this work, we introduce RetroKNN, local reaction template retrieval method to further boost performance template-based systems with non-parametric retrieval. We first build atom-template s...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تربیت مدرس - دانشکده علوم پایه 1391

bekenstein and hawking by introducing temperature and every black hole has entropy and using the first law of thermodynamic for black holes showed that this entropy changes with the event horizon surface. bekenstein and hawking entropy equation is valid for the black holes obeying einstein general relativity theory. however, from one side einstein relativity in some cases fails to explain expe...

Journal: :CoRR 2010
Nitin Bhatia Vandana

The nearest neighbor (NN) technique is very simple, highly efficient and effective in the field of pattern recognition, text categorization, object recognition etc. Its simplicity is its main advantage, but the disadvantages can’t be ignored even. The memory requirement and computation complexity also matter. Many techniques are developed to overcome these limitations. NN techniques are broadly...

Journal: :international journal of agricultural management and development 2013
ebrahim moradi mosayeb pahlavani ahmad akbari hossain mehrabi bashrabadi

2011
L. V. Minh F. Horikiri K. Shibata H. Kuwano

In this paper, a new lead-free piezoelectric (K,Na)NbO3 (KNN) film is presented as a promising, environment-friendly alternative to the conventional piezoelectric thin film materials like PZT, etc. with regard to applying into piezo-MEMS devices in general and micro-energy-harvesting devices in particular. The KNN films deposited by the RF magnetron sputtering deposition system were revealed ex...

Introduction: Breast cancer is the second cause of mortality among women. Early detection is the only rescue to reduce the risk of breast cancer mortality. Traditional methods cannot effectively diagnose tumor since they are based on the assumption of well-balanced dataset.. However, a hybrid method can help to alleviate the two-class imbalance problem existing in the ...

Journal: :Computational Statistics & Data Analysis 2010
Marcus Hutter Minh-Ngoc Tran

A key issue in statistics and machine learning is to automatically select the “right” model complexity, e.g., the number of neighbors to be averaged over in k nearest neighbor (kNN) regression or the polynomial degree in regression with polynomials. We suggest a novel principle the Loss Rank Principle (LoRP) for model selection in regression and classification. It is based on the loss rank, whi...

Journal: :journal of electrical and computer engineering innovations 0
mohsen hasanluo department of computer engineering, urmia branch, islamic azad university, urmia, iran farhad soleimanian gharehchopogh department of computer engineering, urmia branch, islamic azad university, urmia, iran

a successful software should be finalized with determined and predetermined cost and time. software is a production which its approximate cost is expert workforce and professionals. the most important and approximate software cost estimation (sce) is related to the trained workforce. creative nature of software projects and its abstract nature make extremely cost and time of projects difficult ...

2002
Guiwen Hou Jingyue Zhang Jiahong Zhou

In this project we present a heuristic learning process by training ANN (artificial neural network) and KNN (k-nearest neighbor) using the best number of steps, gained from A*, from randomly generated states to the goal. After training ANN and KNN, the mixture of Experts is discussed and the empirical data are collected to demonstrate the feasibility and accuracy of combination of ANN and KNN i...

2011

A model for predicting travel times by mining spatiotemporal data acquired from vehicles equipped with Global Positioning System (GPS) receivers in urban traffic networks is presented. The proposed model, which uses k-nearest neighbour (kNN) non-parametric regression, is compared with models that use historical averages and the seasonal autoregressive integrated moving average (ARIMA) model. Th...

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