El lpresente lproyecto lde linvestigación lse lrealizó len lel lvalle lCasma-Sector lTabon, lcon lla lfinalidad lde levaluar ltres lnematoxicos lpara lel lcontrol lde lnematodos lfitopatogenos len lcultivo lde lmaracuyá l(Passiflora ledullis l.L). Se lutilizó lel ldiseño lexperimental lde lbloques lcompletamente lal lazar l(DBCA) lcon l4 ltratamientos; lT1(Testigo), lT2(Hunter), lT3(Furadan l4F) ly lT4 l(Amauta) l, lcon ltres lrepeticiones l l, lal lfinalizar leste ltrabajo lde linvestigación lse ldeterminó lque lla lpoblación lpromedio lfue lde l432 lhuevos lde lMeloidogyne lincognita len l10 lg lde lraíz ly l l9 lnematodos lde lMeloidogyne lincognita len l100 lg lde lsuelo len lel lcultivo lde lmaracuyá. lCon lrespecto lal lefecto ldel lcontrol lde lnematodos lcon lel luso lde lnematoxicos; lexiste luna ldiferencia laltamente lsignificativa lcon lT1 l(testigo) l, lpero lentre...

This study aims to identify the most optimal supervised learning algorithm to be applied to the prediction of satisfaction of university students. In this study, the IBM SPSS-25.0 software was used to test the reliability of the satisfaction questionnaire and the MATLAB R2021b software through the classification learner technique to determine the supervised learning algorithm. The experimental results determine a Cronbach's Alpha reliability of 0.979, in terms of the classification algorithm, it is validated that the quadratic vector support machine (SVM) has better performance metrics, being correct in 97.8% (accuracy) in the predictions of satisfaction of university students, with a recall (sensitivity) of 96.5% and an F1 score of 0.968. Likewise, when evaluating the classification model by means of the receiver operating characteristic curve (ROC) technique, it is identified that for ...