Improved Learning Algorithms of SLFN for Approximating Periodic Function

The motion picture industry is one of the largest industries worldwide and has significant importance in the global economy. Considering the high stakes and high risks in the industry, forecast models and decision support systems are gaining importance. Several attempts have been made to estimate the theatrical performance of a movie before or at the early stages of its release. Nevertheless, these models are mostly used for predicting domestic performances and the industry still struggles to predict box office performances in overseas markets. In this study, the aim is to design a forecast model using different machine learning algorithms to estimate the theatrical success of US movies in Turkey. From various sources, a dataset of 1559 movies is constructed. Firstly, independent variables are grouped as pre-release, distributor type, and international distribution based on their characteristic. The number of attendances is discretized into three classes. Four popular machine learning algorithms, artificial neural networks, decision tree regression and gradient boosting tree and random forest are employed, and the impact of each group is observed by compared by the performance models. Then the number of target classes is increased into five and eight and results are compared with the previously developed models in the literature.

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Intelligent system of English composition scoring model based on improved machine learning algorithm

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189235 ◽

2020 ◽

pp. 1-11

Author(s):

Jie Liu ◽

Lin Lin ◽

Xiufang Liang

Keyword(s):

Machine Learning ◽

Evaluation System ◽

Intelligent System ◽

Learning Algorithm ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Assessment System ◽

English Composition ◽

Region Extraction ◽

Constraint Model

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.

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The Unlearnable Checkerboard Pattern

Communications of the Blyth Institute ◽

10.33014/issn.2640-5652.1.2.holloway.1 ◽

2019 ◽

Vol 1 (2) ◽

pp. 78-80

Author(s):

Eric Holloway

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Checkerboard Pattern ◽

Simple Task

Detecting some patterns is a simple task for humans, but nearly impossible for current machine learning algorithms. Here, the "checkerboard" pattern is examined, where human prediction nears 100% and machine prediction drops significantly below 50%.

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MENINGKATKAN HASIL BELAJAR IPS SISWA KELAS VC SD NEGERI 164 PEKANBARU DENGAN MENGGUNAKAN METODE PEMBELAJARAN KOOPERATIF NUMBERED HEADS TOGETHER (NHT)

JURNAL PAJAR (Pendidikan dan Pengajaran) ◽

10.33578/pjr.v3i1.6916 ◽

2019 ◽

Vol 3 (1) ◽

pp. 197

Author(s):

Rosita L. Tobing

Keyword(s):

Action Research ◽

Social Studies ◽

Learning Outcomes ◽

Class Actions ◽

Heterogeneous Groups ◽

The Social ◽

Classroom Action Research ◽

Improved Learning ◽

Academic Year

The problem of classroom action research is the low learning outcomes of VC grade 164 students in Pekanbaru. This study aims to improve social studies learning outcomes of VC grade 164 students in Pekanbaru by applying the cooperative method of numbered heads together (NHT). The results of the research and class actions of the Social Studies Course conducted at the VC class SDN 164 Pekanbaru students concluded; Learning outcomes in the first cycle have increased compared to conventional learning. Pre-cycle learning outcomes are an average of 50.25 or sufficient categories; in cycle I, learning outcomes reached an average of 71.75 or in the Good category; in cycle II it increased again by 80.25 or in the Good category; Prasiklus classical completeness is 10 students (25.00%.); the first cycle is 27 students (67.50%); and in the second cycle were 38 students (95.00%). Students who have not been completed are remedial. Observers observed that VC grade 164 students at Pekanbaru Pekanbaru seemed to understand the Numbered Heads Together (NHT) Cooperative Method. They learn and understand shared material in heterogeneous groups of 4-5 students. Based on the results of improved learning studies, the application of the cooperative method of numbered heads together (NHT) succeeded in correcting the problem of the low social studies learning outcomes in VC Class SDN 164 Pekanbaru 2017/2018 Academic Year.

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PENERAPAN STRATEGI MAKE A MATCH UNTUK MENINGKATKAN HASIL BELAJAR IPS KELAS IV SDN 005 KOTO SENTAJO KECAMATAN SENTAJO RAYA

JURNAL PAJAR (Pendidikan dan Pengajaran) ◽

10.33578/pjr.v2i3.5545 ◽

2018 ◽

Vol 2 (3) ◽

pp. 444

Author(s):

Fuji Nengsih

Keyword(s):

Action Research ◽

Initial Data ◽

Learning Outcomes ◽

Primary Schools ◽

Activity Cycle ◽

Student Activity ◽

Teachers And Students ◽

Classroom Action Research ◽

Improved Learning ◽

Daily Test

IPS learning is a science of socio-cultural phenomena, and economics. IPS education in primary schools aims todevelop student potential. This study is a classroom action research that aims to improve the learning processwith the ultimate impact of improved learning outcomes. Data obtained on teacher activity cycle II percentage62.5% and 71% at the second meeting. Cycle II the percentage of teacher activity 83% and 92% at the secondmeeting whereas in student activity on cycle I with percentage 50% and second meeting 62,5% increase in cycleII become 75% and 88% at second meeting cycle II. The activity of teachers and students influences the IPSlearning result data with average views on the initial data 68.3, increased to 79.8 and in the daily test II with anaverage of 89.5. The conclusions in this study are make-match strategies effective in improving IPS learningoutcomes.

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