Leukaemia is one of the cancer type which has disturbed the humans for several years. Even though several screening techniques exists for the classification of the Leukaemia Cancer, microarray analysis still remains as one of the low cost affordable method for every common man to have an initial screening to understand the presence or absence of cancer. For the last two and a half decades, several researches have done the study on Leukaemia microarray classification. Very less research can be seen in the literature which are based on the logarithmic transform of the microaray dataset, especially on Leukaemia microarrays. The results on Leukaemia microarray classification using machine learning techniques after performing logarithmic transforms have outperformed many results in the literature. This improvement in result is obtained with the full set of genes in the Leukaemia microarray without doing any feature selection or dimensionality reduction.