In the field of computer research,the increase of data in result of societal progress has been remarkable,and the management of this data and the analysis of linked businesses have grown in *** are numerous practical ...
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In the field of computer research,the increase of data in result of societal progress has been remarkable,and the management of this data and the analysis of linked businesses have grown in *** are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home *** regression methods in machine learning to segment the data set,examine the major factors affecting it,and forecast home prices is the most popular method for examining pricing *** is challenging to generate precise forecasts since many of the regression models currently being utilized in research are unable to efficiently collect data on the distinctive elements that correlate y with a high degree of house price *** today’s forecasting studies,ensemble learning is a very prevalent and well-liked study *** regression integration computation of large housing datasets can use a lot of computer resources as well as computation time,and ensemble learning uses more resources and calls for more machine support in integrating diverse *** Average Model suggested in this paper uses the concept of fusion to produce integrated analysis findings from several models,combining the best benefits of separate *** Average Model has a strong applicability in the field of regression prediction and significantly increases computational *** technique is also easier to replicate and very effective in regression *** using regression processing techniques,this work creates an average of different regression models using the AM(Average Model)algorithm in a novel *** evaluating essential models with 90%accuracy,this technique significantly increases the accuracy of house price *** experimental results show that the AM algorithm proposed in this paper has lower prediction error than other comparison algorithms,and the prediction accurac
Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous *** assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversit...
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Cultivated potato is a clonally propagated autotetraploid species with a highly heterogeneous *** assemblies of six cultivars including two chromosome-scale phased genome assemblies revealed extensive allelic diversity,including altered coding and transcript sequences,preferential allele expression,and structural variation that collectively result in a highly complex transcriptome and predicted proteome,which are distributed across the homologous *** species contribute to the extensive allelic diversity in tetraploid cultivars,demonstrating ancestral introgressions predating modern breeding *** a clonally propagated autotetraploid that undergoes limited meiosis,dysfunctional and deleterious alleles are not purged in tetraploid *** a quarter of the loci bore mutations are predicted to have a high negative impact on protein function,complicating breeder’s efforts to reduce genetic *** StCDF1 locus controls maturity,and analysis of six tetraploid genomes revealed that 12 allelic variants of StCDF1 are correlated with maturity in a dosage-dependent *** of the complexity of the tetraploid potato genome with its rampant structural variation and embedded deleterious and dysfunctional alleles will be key not only to implementing precision breeding of tetraploid cultivars but also to the construction of homozygous,diploid potato germplasm containing favorable alleles to capitalize on heterosis in F1 hybrids.
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