Difference between revisions of "ISSS608 2017-18 T1 Assign ZHENG MIANYI"
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| − | <p> | + | <p>An epidemic disease broke out in a major metropolitan area, Smartpolis. With provided information such as the city population, disease symptoms, both geographical map and weather of the city and most importantly: microblogs of the residents, I made every efforts to detect the transmission of this disease.</p> |
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| − | + | <div style="color:#0F1940; padding-left: 10px; font-size: 24px; font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;">Data Preparation</div> | |
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| − | + | <p>The initial dataset put the latitude and longitude data together, and the main information is contains in more than 1 million microblogs records. Hence, I separated the geographical digit to two columns, namely latitude and longitude. </p> | |
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| + | <p><b>Subsequently, I chose the key words to select the relevant information. Personally, I prefer a relatively small dataset with higher accuracy rather than a large dataset with lower accuracy. After many trials, I set the target words as:"fever", "chill", "fatigue", "cough", "difficult", "nausea", "vomit", "diarrhea", "lymph" and "throat".</b></p> | ||
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| − | + | Last but not lease, I attempted to explore more information. For instant, is there any initial symptoms before the patients becoming ill? In addition, after viewing the symptoms, we can initially group them into two main problems: flu (those with fever, chills, fatigue, coughing, breathing difficulty, sore throat and enlarged lymph nodes) and stomach problem (those with nausea, vomiting, diarrhea). | |
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Revision as of 12:21, 15 October 2017
| By Zheng Mianyi |
Background
An epidemic disease broke out in a major metropolitan area, Smartpolis. With provided information such as the city population, disease symptoms, both geographical map and weather of the city and most importantly: microblogs of the residents, I made every efforts to detect the transmission of this disease.
Data Preparation
The initial dataset put the latitude and longitude data together, and the main information is contains in more than 1 million microblogs records. Hence, I separated the geographical digit to two columns, namely latitude and longitude.
Subsequently, I chose the key words to select the relevant information. Personally, I prefer a relatively small dataset with higher accuracy rather than a large dataset with lower accuracy. After many trials, I set the target words as:"fever", "chill", "fatigue", "cough", "difficult", "nausea", "vomit", "diarrhea", "lymph" and "throat".
Last but not lease, I attempted to explore more information. For instant, is there any initial symptoms before the patients becoming ill? In addition, after viewing the symptoms, we can initially group them into two main problems: flu (those with fever, chills, fatigue, coughing, breathing difficulty, sore throat and enlarged lymph nodes) and stomach problem (those with nausea, vomiting, diarrhea).
