validation set
<p>Survival advantage and clinicopathological significance of microRNA-22 in cancers: a meta-analysis</p>
... training set; V, validation set; NR, not reported; Co, colon set; Re, rectal set; “ - ” , not mention; ISH, in situ hybridization; SC, survival curve; OS, overall survival; PFS, ...
14
<p>Construction and validation of a seven-microRNA signature as a prognostic tool for lung squamous cell carcinoma</p>
... Results: A total of 316 miRs were differentially expressed between LUSC and matched healthy lung tissues in the training set. Following the univariate and multivariate Cox regression analysis, we found that seven ...
9
Diagnostic value of multiple tumor-associated autoantibodies in lung cancer
... training set we mea- sured the expression levels of AABs in 100 non-small-cell lung cancer (NSCLC) patients and 60 healthy controls by using ELISA detection ...blinded validation was subsequently performed ...
13
Computational Multivariate Regression and Validation Analysis on a Set of AKT kinase Inhibitors
... a set of 61 pyridine based analogs to study the influence of physico-chemical properties on AKT ...complete set as a 51 molecule training set and a 6 molecule validation set based on ...
9
Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma
... and validation sets. Training set samples (N = 24) were prospectively collected from surgeries performed at AC Camargo Hospital, SP (N = 17 lung adenocarcinoma samples and 7 histologically normal lung ...
15
A meta stacked ensemble probabilistic classifier
... Logistic Regression with an initial accuracy of 0.93 and Linear SVM with the observed accuracy of 0.9373 were pruned out of the race for parameter tuning. Later ensemble parameter tuning was performed by adopting the ...
7
Neural Machine Translation Techniques for Named Entity Transliteration
... the validation set fails to reach a new minimum for 5 consecutive val- idation ...the validation score does not improve over the current best ...
6
QSAR analysis and validation studies of XIAP inhibitors
... the set as a 68 molecule training set and a 6 molecule validation set based on hierarchical clustering after rejecting outliers from the data ...training set was made according to the ...
6
A nomogram for individualized estimation of survival among adult patients with adrenocortical carcinoma after surgery: a retrospective analysis and multicenter validation study
... training set, comprised of 404 patients diagnosed between January 2007 and December 2015, and an internal validation set, com- prised of 318 patients diagnosed between January 1988 and December ...
13
Near Infrared Spectroscopic Analysis of Hemoglobin with Stability Based on Human Hemolysates Samples
... the validation set; they were not involved in the modeling optimization ...calibration set, modeling prediction set, and validation ...first validation were per- formed in the ...
5
Practical-ML
... (smaller than the true error rate) since the validation set is used to select the final model. • After assessing the final model with the test set, YOU MUST NOT tune the[r] ...
25
Approach to Chemometrics Models by Artificial Neural Network for Structure: First Applications for Estimation Retention Time of Doping Agent
... The GA-PLS, GA-KPLS, and L-M ANN modeling were applied to predict the retention time of 103 doping agents. High correlation coefficients and low prediction errors confirmed the good predictability of models. Application ...
23
CHEMOMETRICS ASSISTED AND RP HPLC METHODS FOR QUANTIFICATION OF NETUPITANT AND PALONOSETRON HYDROCHLORIDE BY QBD APPROCH: DEVELOPMENT AND VALIDATION
... of validation set ...the validation set and it also provides information about how well the method will predict the future ...the validation set it can be found that the residual ...
25
QSAR AND DOCKING STUDIES OF CHLORPROPAMIDE DERIVATES
... a diverse array of compounds. 4 The present work focuses on the molecular docking analysis of chlorpropamide and its analogues against protein. 5 This work was carried out by molecular docking studies to determine ...
12
Bayesian Polytrees With Learned Deep Features for Multi-Class Cell Segmentation.
... Figure 13 shows the DSC of the three methods when SegNet features are used with variable numbers of the training sam- ples. Table II shows the average Dice similarity coefficients for each of the three methods and for ...
14
Bayesian polytrees with learned deep features for multi-class cell segmentation
... Using polytrees with scale-space differential invariant fea- tures (Fig. 13) suggests that depending on the choice of model features and parameters, it can outperform SegNet, even though the latter is trained on a much ...
16
A COMPARATIVE GROUP QSAR AND MOLECULAR DOCKING STUDIES OF 4 THIAZOLIDINONE CONTAINING INDOLIN 2 ONE MOIETY AS VGEFR INHIBITORS
... Partial Least Square (PLS) Analysis: Partial least squares regression, also called projection to latent structure can be applied to establish a predictive model even if the features are highly correlated. This makes PLS ...
10
Open source R for applying machine learning to RPAS remote sensing images
... Future investigations will limit mixing by careful selec- tion of single pixels for both training and validation. This will decrease the size of the sets, but will increase the purity of pixel class and provide ...
7
Original Article Value of epithelioid morphology and PDGFRA immunostaining pattern for prediction of PDGFRA mutated genotype in gastrointestinal stromal tumors (GISTs)
... a validation cohort spanning the morphological and genotypic spectrum of GISTs was used to predict the PDGFRA genotypic status based on the histomorphology of tumors and their PDGFRA immunostaining ...
8
Estimating hill country rainfall without full data sets for the Manawatu River catchment : a thesis presented in partial fulfillment of the requirements for the degree of Master of Resource and Environmental Planning at Massey University, Turitea, New Zealand
... Incorporating auxiliary data sets in the estimation, especially topographic variables that have great impact on the spatial variation of rainfall, is another way to estimate rainfall closer to the reality by having more ...
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