A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity

Abstract

Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. The optimization of algorithms got abundant attention of researchers being a core component for deploying the machine learning model (MLM) abled to learn the parameters in significant ways for the given data. Modeling crop productivity through innumerable agronomical constraints has become a crucial task for evolving sustainable agricultural policies. The cross-sectional datasets of 26430 (D1) crop-cut experiments are taken by 2nd-stage area frame sampling, collected from crop reporting service. This research is taken as follows: firstly three more effective numerical optimized datasets are generated (D1, D2, and D3) from D1 by taking the centroid points of features which decrease the sample size; secondly MLM is integrated with the traditional statistical models (TSMs) for multiple linear regression (MLR), and thirdly decision tree regression (DTR) and random forest regression (RFR) are deployed to get the optimized models able to predict the wheat productivity well with 75% datasets to train and 25% to test the model using the evaluation metrics (R2, RMSE), information criterion (AIC) with weights (AICW), evidence ration (E.R), and decompositions of prediction error. The MLR outperformed for MLM than TSM. The performance capability of MLM and TSM got upswing for generated datasets. RFR got optimized and superperformed for D1, D2, D3, and D4. This study demonstrated strong evidences for deploying MLM for prediction of wheat productivity as an alternative of traditional statistical modeling.

Optimizations of Modified Machine Learning Algorithms Using K-Fold Cross Validations for Wheat Productivity: A Hyper Parametric Approach

“…Its exigent need of the time is to develop an optimized model capable to predict the wheat productivity on the reliable statistics which would help us to attain the non-assurance and assurance of future food demand (Sharma et al, 2015). Islam and Shehzad (2022) presented the study on the large datasets for building the machine learning and statistical models for the wheat productivity in Pakistan based on crosssectional record.…”

“…This study conducted in Punjab, which is 2 nd largest province of Pakistan accounted 76% share in total wheat cultivated area (Islam, 2022) The experiment is performed using Scikit Learn (Sklean), a Python's key library. Islam and Shehzad (2022), Islam et al (2021) described the centroid clustering scheme and introduced the following new generated datasets (Table 2) with the aims to get the most optimized set of features for models, based on centralization of dataset at village, tehsils and district level datasets.…”

Analyzing the Impact of Subsectors and Population Growth on Agricultural Sector in Pakistan

“…Multiple agriculture issues plague Pakistan's economy, including poor irrigations system, bad infrastructure, traditional farming techniques/methods, poor supply of agriculture inputs and bad financial condition of farmers etc. Despite its impressive agricultural output, Pakistan faces significant food insecurity, affecting half of the population according to the World Food Program (Islam & Shehzad, 2022;Islam et al, 2023;Shiferaw et al, 2013). The increasing population and agricultural production put immense pressure on agriculture sector.…”

Growth Analysis of Production of Food Crops and Population Growth for Food Security in Pakistan

“…Agriculture sector was contributing 53 % to Pakistan's GDP in 1949, but over time the share of agriculture in Pakistan's economy has reduced to 19.2 %, which has also reduced the share of the labor force engaged in agriculture from 65 % to 38.5 %. The growth rate of the population in Pakistan is high as compared to neighboring South Asian countries [7]. The high growth rate of the population is leading Pakistan towards a food shortage and may affect the adequate food availability for the growing population [7,8].…”

“…The growth rate of the population in Pakistan is high as compared to neighboring South Asian countries [7]. The high growth rate of the population is leading Pakistan towards a food shortage and may affect the adequate food availability for the growing population [7,8]. According to UNO, MDGs, food security has become a global threat to the world, due to the expansion of the world population.…”