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IsaacMwendwa authored Aug 10, 2021
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<html lang="en">

<head>
<title>Predictive Analysis of Wage Employment Based on Economic Growth in Kenya</title>
<title>Predictive Analysis of Productive Employment Based on Economic Growth in Kenya</title>
<meta charset="utf-8">
<meta name="viewport" content="width=device-width, initial-scale=1">
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<a class="navbar-brand" href="#">Predictive Analysis of Wage Employment Based on Economic Growth in Kenya</a>
<a class="navbar-brand" href="#">Predictive Analysis of Productive Employment Based on Economic Growth in Kenya</a>
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<div class="col-sm-8 text-left">
<h1>Predictive Analysis of Wage Employment</h1>
<p>Welcome to do a predictive analysis of wage employment based on economic growth in Kenya. Specifically, we
<h1>Predictive Analysis of Productive Employment</h1>
<p>Welcome to do a predictive analysis of productive employment based on economic growth in Kenya. Specifically, we
will be predicting the number of people earning below the poverty line
(Wage_bracket_0_to_10000). This group is referred to as the working poor. Moreover,
we will also predict the total number of people in employment
(Wage_bracket_0_to_10000), per industry. This group is referred to as the working poor. Moreover,
we will also predict the total number of people in employment per industry.
</p>
<p>This predictive analytics project seeks to provide actionable insights to drive policy making and action,
which will guarantee the attainment of Sustainable Development Goals (SDGs) Number 8, which is to "Promote
sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all."
</p>
<p>The prediction problem is formulated as: Given the economic growth indicators (Contribution by GDP, Growth of GDP)
by sector or industry, predict the number of people in non-productive employment (working poor) and the total number of people
in employment per sector/industry.
</p>
<p>The prediction problem is formulated as: Given the economic growth indicators
and the number of people in the working poor bracket/ total number in employment, at
the prior time step(year), predict the number in the current time step(year) </p>
<h3>Uploading CSV Document</h3>
<p>Please proceed to download sample test CSV files containing input data from the left sidebar</p>
<p>Upload the downloaded file to get the predictions for the next year</p>
<p>The model will then predict the number of people in Wage_bracket_0_to_10000, and also the
<p>The system will then use predictive models to predict the number of people in Wage_bracket_0_to_10000, and also the
Total_number_in_wage_employment</p>
<p>The results gotten are for each Industry/Sector e.g Agriculture, Manufacturing, Education e.t.c</p>
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<div class="col-sm-2 sidenav">
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<p><b>Input Variables</b></p>
<p>Year</p>
<p>Wage bracket 0 to 9999</p>
<p>Total number in wage employment</p>
<p>Contribution to GDP</p>
<p>Growth of GDP</p>
<p>Industry (Sectors)</p>
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</div>

<footer class="container-fluid text-center">
<p>Predictive Analysis of Wage Employment in Kenya</p>
<p>Predictive Analysis of Productive Employment in Kenya</p>
</footer>
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