Establecer una secuencia efectiva de aprendizaje a través de un modelo sistemático de búsqueda de construcción de datos
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Fecha
2021
Profesor/a Guía
Facultad/escuela
Idioma
es
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Editor
Universidad Andrés Bello
Nombre de Curso
Licencia CC
Licencia CC
Resumen
En esta tesis, hemos establecido una secuencia efectiva de aprendizaje a través de un modelo
sistemático de búsqueda de construcción de datos mediante la plataforma de Yahoo! Answers en
el contexto de predicción de género y edad.
Para obtener esta secuencia, se segmentaron los datos de entrenamiento según el género y año de
nacimiento de cada usuario en lotes. Para seleccionar el mejor lote se implementó un algoritmo
greedy considerando el mayor valor de la métrica macropromedio.
Como resultado se obtuvo un curriculum o secuencia efectiva de aprendizaje, la cual fue verificada
mediante el entrenamiento de un modelo de Bayes. Para comprobar el curriculum de aprendizaje
se realizaron 2 experimentos, en el primer experimento se entrenó el modelo sin el curriculum, es
decir, con todos los datos de los usuarios (329.025) ejemplos y en el segundo experimento se
entrenó el modelo con el curriculum (11.176 ejemplos). El resultado final fue que ambos modelos
tuvieron el mismo rendimiento de predicción, sin embargo, en el segundo experimento se
necesitaron menos datos, por lo que su entrenamiento fue más rápido y eficiente, comprobando de
esta manera la efectividad del curriculum.
In this thesis, we have established an effective learning sequence through a systematic search model of data construction using the Yahoo! Answers in the prediction context of gender and age. To obtain this sequence, the training data was segmented according to the gender and year of birth of each user in batches. To select the best batch, a greedy algorithm was implemented considering the highest value of the macro-average metric. As a result, an effective learning sequence or curriculum was obtained, which was verified by training a Bayes model. To check the learning curriculum, 2 experiments were carried out, in the first experiment the model was trained without the curriculum, that is, with all the data of the users (329.025 examples) and in the second experiment the model was trained with the curriculum 11.176 examples). The final result was that both models had the same prediction performance, however, in the second experiment less data was needed, so their training was faster and more efficient, thus checking the effectiveness of the curriculum.
In this thesis, we have established an effective learning sequence through a systematic search model of data construction using the Yahoo! Answers in the prediction context of gender and age. To obtain this sequence, the training data was segmented according to the gender and year of birth of each user in batches. To select the best batch, a greedy algorithm was implemented considering the highest value of the macro-average metric. As a result, an effective learning sequence or curriculum was obtained, which was verified by training a Bayes model. To check the learning curriculum, 2 experiments were carried out, in the first experiment the model was trained without the curriculum, that is, with all the data of the users (329.025 examples) and in the second experiment the model was trained with the curriculum 11.176 examples). The final result was that both models had the same prediction performance, however, in the second experiment less data was needed, so their training was faster and more efficient, thus checking the effectiveness of the curriculum.
Notas
Tesis (Magíster en Gestión de Tecnologías de la Información y Telecomunicaciones)
Palabras clave
Sitios Web, Evaluación, Aprendizaje de Máquina, Modelo Predictivo