Before making any kind of financial investment, stock market analysis is frequently conducted using the common methods of fundamental analysis and technical analysis. Machine learning algorithms have extremely limited application in fundamental analysis, although they are widely employed in technical analysis. When performing technical analysis, the majority of investors use a methodical approach that involves plotting Japanese candles and obtaining important information. When plotted individually as a time series data, some of these candles provide useful information, but not all candles. The question is if certain candles aren't useful when used individually, will they still be useful when used in groups? When plotted in groups, certain known groups of candles can offer useful information. More patterns would definitely need to be found. It would also be intriguing to learn whether these trends tend to repeat themselves. Finally, regardless of the type of candle, generalized rules must be discovered. A semi-supervised approach was the best option to study this. Following this investigation, we actually discovered several helpful guidelines that provide investors with greater knowledge.