sum-of-square-error
Big Data Analytic of Nigeria Population Census Data using MapReduce and K Means Algorithm
... MapReduce framework is a parallel processing framework that parallelizes both data and computation. It consists of both map phase and reduce phase. K-means implementation on MapReduce can aid k-means to scale well with ...
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Modelling and PSO Fine-tuned PID Control of Quadrotor UAV
... In this simulation, initially, ϕ, θ, and ψ are set at 0.2 radian. The simulation times is set from 0 to 20s and updates every 100Hz. Desired ϕ, θ, and ψ are set to 0 radian, while desired z is set at 10 meters. Number of ...
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Stability analysis for yield and quality traits in wheat (Triticum aestivum L.)¬¬¬¬
... pooled error. The regression analysis showed that the mean sum of square due to environment (Linear) was highly significant for all the trait when tested against pooled error, hence ...
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The Identification of Car Combustion Engine Category on Exhaust Emissions Data Pattern Base Using Sum Square Error Method
... The next step was Fast Fourier Transform (FFT) and was conducted to change the sensor detection data of the time domain into the frequency domain with certain magnitude values, as shown in Fig. 3. Stages of making data ...
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Learning Rates in Generalized Neuron Model for Short Term Load Forecasting
... ANN, error functions, learning algorithms, hidden ...the sum square error gradient by applying STLF with the help of generalized neuron model decreases the non adaptive load and adaptive load ...
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Effect of major Orthopedic Surgery on the nutritional status of the patients
... Tables for analysis of transferrin in Bilateral replacement group Table – 44 Type III Sum of Source Intercept age_rec Error Squares df Mean Square F Sig... Tables for comparison between [r] ...
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On the sensitivity of transversal RLS algorithms to random perturbations in the filter coefficients
... Transversal Recursive Least Squares (RLS) algorithms estimate filter coefficients which minimize the accumulated sum of the square of the error residuals termed the error power.. In this[r] ...
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An Efficient Algorithm to Design Nearly Perfect-Reconstruction Two-Channel Quadrature Mirror Filter Banks
... The error measure to be minimized is formulated as a weighted sum of pass-band error and stop-band residual energy of low-pass prototype filter and the square error of the distortion ...
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ENHANCEMENT OF AES ALGORITHM BASED ON CHAOTIC MAPS AND SHIFT OPERATION FOR IMAGE ENCRYPTION
... The experimental results show the accuracy of EFKCN [4] not yet close to 92.7 percent by fourth iteration (Table 1). Moreover, with t = 4, the accuracy of EFKCN is 75.22 percent. Meanwhile, the accuracy of FKCN [1] with ...
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Process improvement to the anodize line through design of experiments
... Analysis of Variance 18 ANOVA of Freedom Degrees Sum of Squares Model, Error, Total Model, Error, Total Model Mean Square Error Mean Square F Ratio Prob>F "The analysis of variance obser[r] ...
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SECRET DATA HIDING BY OPTIMIZING GENERAL SMOOTHNESS DIFFERENCE EXPANSION BASED METHOD
... Mean Square Error, Mean Absolute Error, Sum Square Error and Root Mean Square Error are used to access the ...
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Sum Square Prime Labeling for Some Path Related Graphs
... Sum square prime labeling of a graph is the labeling of the vertices with 0,1,2---------,p-1 and the edges with square of the sum of the labels of the incident ...admits sum ...
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Mean Sum Square Prime Labeling of Some Snake Graphs
... K, Sum Square Prime Labeling of Some Path Related Graphs, International Journal of Research in Engineering and Applied ...K, Sum Square ...
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The recovery of inter‐block information in balanced incomplete block designs
... This latter sum of squares can best be computed by taking the difference of the total sum of squares for blocks (ignoring varieties) and the component of this sum of square[r] ...
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Robustness of Bootstrap Estimators to Influential Observations
... ABSTRACT: The existence of outliers in the original sample may create problem to the classical bootstrapping estimates. There is possibility that the bootstrap samples may contain more outliers than the original dataset ...
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Analyzing Cervical Cancer by using an Ensemble Learning Approach based on Meta Classifier
... In this experiment, we explored the cervical cancer data by apply- ing Correlation-based Feature Selection (CFS) methods with many subset classifiers, ranking most significant features with different feature selection ...
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MEAN SUM SQUARE PRIME LABELING OF SOME CYCLE RELATED GRAPHS
... Cite This Article: Sunoj B S, and Mathew Varkey T K. (2017). “MEAN SUM SQUARE PRIME LABELING OF SOME CYCLE RELATED GRAPHS.” International Journal of Engineering Technologies and Management Research, 4(12), ...
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Studies on amyloglucosidase from rhizopus delemar
... The standard error of a mean is obtained by dividing the square root of tho error variance standard deviation by the square root of the number of experimental points#... variance Is comp[r] ...
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RMSE (Root Mean Square Error), respectively.
... In this research, we are interest in time series analysis with the most popular method, that is, the Box and Jenkins method [3]. The result model of this method is quite accurate compared to other methods and can be ...
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Absolute Difference of Square Sum and Sum Mean Prime Labeling of Some Path Related Graphs
... of square sum and sum mean prime labeling of a graph is the labeling of the vertices with {1,2---,p} and the edges with absolute difference of the mean of the squares of the labels of the incident ...
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