• Title/Summary/Keyword: Forward selection

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Evaluating Variable Selection Techniques for Multivariate Linear Regression (다중선형회귀모형에서의 변수선택기법 평가)

  • Ryu, Nahyeon;Kim, Hyungseok;Kang, Pilsung
    • Journal of Korean Institute of Industrial Engineers
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    • v.42 no.5
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    • pp.314-326
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    • 2016
  • The purpose of variable selection techniques is to select a subset of relevant variables for a particular learning algorithm in order to improve the accuracy of prediction model and improve the efficiency of the model. We conduct an empirical analysis to evaluate and compare seven well-known variable selection techniques for multiple linear regression model, which is one of the most commonly used regression model in practice. The variable selection techniques we apply are forward selection, backward elimination, stepwise selection, genetic algorithm (GA), ridge regression, lasso (Least Absolute Shrinkage and Selection Operator) and elastic net. Based on the experiment with 49 regression data sets, it is found that GA resulted in the lowest error rates while lasso most significantly reduces the number of variables. In terms of computational efficiency, forward/backward elimination and lasso requires less time than the other techniques.

Geometrical description based on forward selection & backward elimination methods for regression models (다중회귀모형에서 전진선택과 후진제거의 기하학적 표현)

  • Hong, Chong-Sun;Kim, Moung-Jin
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.5
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    • pp.901-908
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    • 2010
  • A geometrical description method is proposed to represent the process of the forward selection and backward elimination methods among many variable selection methods for multiple regression models. This graphical method shows the process of the forward selection and backward elimination on the first and second quadrants, respectively, of half circle with a unit radius. At each step, the SSR is represented by the norm of vector and the extra SSR or partial determinant coefficient is represented by the angle between two vectors. Some lines are dotted when the partial F test results are statistically significant, so that statistical analysis could be explored. This geometrical description can be obtained the final regression models based on the forward selection and backward elimination methods. And the goodness-of-fit for the model could be explored.

Link Adaptation and Selection Method for OFDM Based Wireless Relay Networks

  • Can, Basak;Yomo, Hiroyuki;Carvalho, Elisabeth De
    • Journal of Communications and Networks
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    • v.9 no.2
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    • pp.118-127
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    • 2007
  • We propose a link adaptation and selection method for the links constituting an orthogonal frequency division multiplexing (OFDM) based wireless relay network. The proposed link adaptation and selection method selects the forwarding, modulation, and channel coding schemes providing the highest end-to-end throughput and decides whether to use the relay or not. The link adaptation and selection is done for each sub-channel based on instantaneous signal to interference plus noise ratio (SINR) conditions in the source-to-destination, source-to-relay and relay-to-destination links. The considered forwarding schemes are amplify and forward (AF) and simple adaptive decode and forward (DF). Efficient adaptive modulation and coding decision rules are provided for various relaying schemes. The proposed end-to-end link adaptation and selection method ensures that the end-to-end throughput is always larger than or equal to that of transmissions without relay and non-adaptive relayed transmissions. Our evaluations show that over the region where relaying improves the end-to-end throughput, the DF scheme provides significant throughput gain over the AF scheme provided that the error propagation is avoided via error detection techniques. We provide a frame structure to enable the proposed link adaptation and selection method for orthogonal frequency division multiple access (OFDMA)-time division duplex relay networks based on the IEEE 802.16e standard.

Performance Analysis of Decode-and-Forward Relaying Based on Optimal Relay Selection (디코딩 후 전달방식에서 최적의 중계노드 선택방법에 대한 링크레벨 성능분석)

  • Lee, In-Ho;Kim, Dong-Woo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1A
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    • pp.36-43
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    • 2008
  • In this paper, we propose an optimal relay selection scheme for decode-and-forward relaying systems. The optimal relay selection minimizes the number of time slots used to relay source's signal and maximizes an end-to-end signal-to-noise ratio. However, decode-and-forward relaying systems require additional overhead for the optimal relay selection. Assuming independent and identically distributed Rayleigh fading channels, we provide exact and closed-form expressions for the outage probability of capacity and the bit error rate for decode-and-forward relaying systems with the optimal relay selection. It is shown that the analytic results are perfectly matched with the simulated ones. When the numbers of relay nodes are 2, 4, and 8, and the numbers of time slots for overhead are 1, 2, and 4, respectively, the proposed system achieves 1 dB, 2 dB, and 3 dB gains at 1% bit error rate, respectively, and 0.5 dB, 4 dB, and 12 dB gains at 1% outage probability for 1 bps/Hz, respectively, over the conventional decode-and-forward relaying system.

Diagnosis of Alzheimer's Disease using Wrapper Feature Selection Method

  • Vyshnavi Ramineni;Goo-Rak Kwon
    • Smart Media Journal
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    • v.12 no.3
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    • pp.30-37
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    • 2023
  • Alzheimer's disease (AD) symptoms are being treated by early diagnosis, where we can only slow the symptoms and research is still undergoing. In consideration, using T1-weighted images several classification models are proposed in Machine learning to identify AD. In this paper, we consider the improvised feature selection, to reduce the complexity by using wrapping techniques and Restricted Boltzmann Machine (RBM). This present work used the subcortical and cortical features of 278 subjects from the ADNI dataset to identify AD and sMRI. Multi-class classification is used for the experiment i.e., AD, EMCI, LMCI, HC. The proposed feature selection consists of Forward feature selection, Backward feature selection, and Combined PCA & RBM. Forward and backward feature selection methods use an iterative method starting being no features in the forward feature selection and backward feature selection with all features included in the technique. PCA is used to reduce the dimensions and RBM is used to select the best feature without interpreting the features. We have compared the three models with PCA to analysis. The following experiment shows that combined PCA &RBM, and backward feature selection give the best accuracy with respective classification model RF i.e., 88.65, 88.56% respectively.

Opportunistic Relay Selection for Joint Decode-and-Forward Based Two-Way Relaying with Network Coding

  • Ji, Xiaodong;Zheng, Baoyu;Zou, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.9
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    • pp.1513-1527
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    • 2011
  • This paper investigates the capacity rate problems for a joint decode-and-forward (JDF) based two-way relaying with network coding. We first characterize the achievable rate region for a conventional three-node network scenario along with the calculation of the corresponding maximal sum-rate. Then, for the goal of maximizing the system sum-rate, opportunistic relay selection is examined for multi-relay networks. As a result, a novel strategy for the implementation of relay selection is proposed, which depends on the instantaneous channel state and allows a single best relay to help the two-way information exchange. The JDF scheme and the scheme using relay selection are analyzed in terms of outage probability, after which the corresponding exact expressions are developed over Rayleigh fading channels. For the purpose of comparison, outage probabilities of the amplify-and-forward (AF) scheme and those of the scheme using relay selection are also derived. Finally, simulation experiments are done and performance comparisons are conducted. The results verify that the proposed strategy is an appropriate method for the implementation of relay selection and can achieve significant performance gains in terms of outage probability regardless of the symmetry or asymmetry of the channels. Compared with the AF scheme and the scheme using relay selection, the conventional JDF scheme and that using relay selection perform well at low signal-to-noise ratios (SNRs).

Optimal Duplex Selection for Decode and Forward Relay Systems with Power Allocation

  • Kwon, Taehoon;Lim, Sungmook
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.12
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    • pp.5347-5360
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    • 2016
  • In decode and forward relay systems, choosing the duplex mode is an important factor to the performance. To satisfy the performance requirement, self-interference must be mitigated for the full-duplex relay (FDR), and the resource efficiency must be increased for the half-duplex ratio (HDR). Therefore, if a wise scheme to consider these two factors exists, decode and forward relay systems are used more effectively. This study proposes a new duplex selection scheme for decode and forward relay systems. The proposed duplex selection scheme chooses the better duplex mode according to the channel statistical conditions with optimal power allocation. The simulation results show that the proposed duplex scheme with optimal power allocation has lower outage probability than the FDR and the HDR.

Partial Relay Selection for Decode and Forward over Rayleigh Fading Channels (레일리페이딩 환경에서 복호 후 재전송방식을 위한 부분적 릴레이 선택방식 연구)

  • Bao, Vo Nguyen Quoc;Kong, Hyung-Yun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.7A
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    • pp.523-529
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    • 2009
  • This paper provides closed form expressions for the evaluation of the end-to-end outage probability, symbol error rate, bit error rate and average capacity of the partial-based Decode-and-Forward (DF) relay selection scheme with an arbitrary number of relays. In a comparison with the performance of systems that exploit Amplify-and-Forward (AF), it can be seen that the performance of our proposed protocol converges to that of partial-based AF relay selection in high SNR regime. We also perform Monte-Carlo simulations to validate the analysis.

Exact and Approximate Symbol Error Probability of cooperative systems with best relay selection and all participating relaying using Amplify and Forward or Decode and Forward Relaying over Nakagami-m fading channels

  • Halima, Nadhir Ben;Boujemaa, Hatem
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.1
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    • pp.81-108
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    • 2018
  • In this paper, we derive the theoretical Symbol Error Probability (SEP) of cooperative systems with best relay selection for Nakagami-m fading channels. For Amplify and Forward (AF) relaying, the selected relay offers the best instantaneous Signal to Noise Ratio (SNR) of the relaying link (source-relay-destination). In cooperative networks using Decode and Forward (DF), the selected relay offers the best instantaneous SNR of the link between the relay and the destination among the relays that have correctly decoded the transmitted information by the source. In the second part of the paper, we derive the SEP when all participating AF and DF relaying is performed. In the last part of the paper, we extend our results to cognitive radio networks where there is interference constraints : only relays that generate interference to primary receiver lower than a predefined threshold T can transmit. Both AF and DF relaying with and without relay selection are considered.