## 2 Materials and Methods
### Data Cleaning and Preprocessing
Factors like underreporting by parents, limited awareness of early developmental challenges, and disparities in access to health and education services further contribute to this imbalance. The implications of this imbalancehave been recognized, and appropriate measures were considered to address its effects on analysis and predictions. Figure 2 presents six grouped bar charts comparing the count of children with and without learning difficulties across various categories. Blue bars represent children without learning difficulties, while red bars indicate children with learning difficulties. The charts show differences in experiences and demographics, highlighting factors and patterns that might contribute to learning difficulties. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Independent Variables** & **Variables** & **Description** & **Values** & **Data Type** \\ \hline UCD2A & Removed\_privileges & Took away privileges & YES, NO & Categorical \\ \hline UCD2C & Shook\_child & Shook child & YES, NO & Categorical \\ \hline UCD2K & Beat\_hard & Beat child as hard as one could & YES, NO & Categorical \\ \hline HL4 & Sex & Sex & MALE, FEMALE & Categorical \\ \hline windex5 & Wealth\_index & Wealth index quintile & \
\begin{tabular}{c} Richest, Fourth, Second, \\ Poorest, Middle \\ \end{tabular} & Categorical \\ \hline wheel & Mother’s\_education & Mother’s education &
\begin{tabular}{c} Higher secondary+, \\ Primary, Secondary, \\ Pre-primary or none \\ \end{tabular} & Categorical \\ \hline UCD2H & Called\_dumb\_lazy & Called child dumb and lazy & YES, NO & Categorical \\ \hline AN4 & Child’s\_weight & Child’s weight (kilograms) & 1.1-35.8 kg & Numerical \\ \hline WAP & Weight\_age\_P & Weight-for-age percentile & 0.0–89.5 & Numerical \\ \hline
**Dependent Variables** & & & & \\ \hline
**MICS variables** & **Variable** & **Description** & **Values** & **Data Type** \\ \hline UCP17 & Learning\_skill & \
\begin{tabular}{c} Compared with children of the \\ same age, child has difficulty \\ learning things \\ \end{tabular} &
\begin{tabular}{c} NO DIFFICULTY, HAS \\ DIFFICULTY \\ \end{tabular} & Categorical \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Definition of variables or features list. Figure 2: Analysis of categorical features. The distribution of the variables Child's_weight and Weight_age_P was examined using density plots and boxplots to identify skewness, central tendencies, and outliers in Figure 3a,b. For Weight_age_P, the density plot revealed a highly right-skewed distribution, with values concentrated near zero and a long tail extending toward higher values. The boxplot confirmed this pattern, showing a narrow interquartile range (IQR) and numerous outliers above the upper whisker. To address this skewness and reduce the influence of outliers, a log transformation was applied, which stabilized variance and improved data symmetry. In contrast, the Child's_weight variable exhibited an approximately symmetric distribution, as seen in both the density plot and boxplot. The IQR captured most of the data, with the median centrally located. Although a few outliers were observed outside the whiskers, their impact on the overall distribution was minimal, and no transformation was required.